Signals are promoted only when they change a judgment, strengthen a convergence, or create a time-sensitive advisory move.
Most recent successful retrieval (partial coverage): 28 Sep, 14:53 Beirut Packet generated 28 Sep, 14:53 Beirut Page built 28 September 2026, 14:53 Beirut
1do now
8open decisions
12signals in view
12precursors
72sources tracked
4stale · 4 errors
Today
Recent source-dated developments; a signal alone does not change advice
PUBLISHED28 Sep, 07:00
Action Forcing: Training World Models on Unsupervised Video by Recovering Underlying Egomotion Bases
preprint; not peer reviewed
arXiv:2609.30595v1 Announce Type: new Abstract: Synchronised action annotations are needed to train controllable world models and these datasets remain elusive. Existing approaches make use of instrumented platforms with calibrated sensors, costly manual annotation, or latent-action models which lack grounding. We…
Why you may careCould improve how you evaluate or monitor agents; the method and results need independent checking before adoption.
Next checkCheck the measured outcome, comparison, limits, and whether it applies to a decision you own. Until then, treat it as a lead.
PUBLISHED28 Sep, 07:00
VLALight: Lightweight Vision-Language-Action Models for Emergency-Aware Traffic Signal Control
preprint; not peer reviewed
arXiv:2609.30709v1 Announce Type: new Abstract: Traffic signal control (TSC) is essential for mitigating urban congestion. Recent advances in vision-language models (VLMs) enable richer interpretation of intersection scenes, opening new opportunities for visual-context-aware TSC. However, the loose coupling and…
Why you may careA reported deployment case may be relevant; its results may not transfer to your workflow or operating conditions.
Next checkCheck the measured outcome, comparison, limits, and whether it applies to a decision you own. Until then, treat it as a lead.
PUBLISHED28 Sep, 07:00
From Mono to Stereo: Accelerating Binocular Gaussian Splatting via Reprojection and Selective Patching
preprint; not peer reviewed
arXiv:2609.30741v1 Announce Type: new Abstract: Binocular rendering requires two nearby views of the same scene and therefore repeats substantial visibility and shading work. We present a 2D Gaussian Splatting (2DGS) pipeline that fully renders a dominant-eye RGB image and an alpha-weighted depth proxy, reprojects…
Why you may careCould improve how you evaluate or monitor agents; the method and results need independent checking before adoption.
Next checkCheck the measured outcome, comparison, limits, and whether it applies to a decision you own. Until then, treat it as a lead.
WATCHDECISION PROPOSED
Treat OpenRouter's DeepSeek Latest price/catalog revision as a route-specific cost signal; verify an exact pinned model/version before updating any cost assumption or routing decision.
OpenRouter's current pages map Pro Latest to V4 Pro 0813 at $3.78/M output tokens and Flash Latest to V4.1 Flash at $0.60/M. The prior catalog snapshot differs materially, but latest aliases and slight page/API discrepancies prevent a like-for-like tariff conclusion.
Say this to MJ agent workflows, USEK research, and GCC deployment cost planningBefore relying on a DeepSeek Latest route for cost estimates, pin the exact model version and check the current provider/router tariff against the earlier catalog snapshot. No routing change is proposed from this listing alone.
Next moveCompare the pinned V4 Pro 0813 and V4.1 Flash tariffs with any direct-provider price sheet and calculate cost per successful representative task before changing a budget or route.
What would change this judgment?
The apparent increase disappears when comparing the same pinned model version, or direct provider pricing and a fixed-task cost-per-success measurement show no meaningful change for MJ's workload.
Labs, models & tooling33/34 live
97%
Research13/13 live
100%
Expert intelligence6/6 live
100%
Policy, capital & adoption14/17 live
82%
Talent2/2 live
100%
Grok / X precursor scoutLatest attempt 24 Sep, 10:53 Beirut
ClinicalTrials.gov AI studies: Client error '403 Forbidden' for url 'https://clinicaltrials.gov/api/v2/studies?query.term=artificial%20intelligence%20OR%20machine%20learning&pageSize=100&format=json'
For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/403
Congress — frontier technology bills and actions: credential required: CONGRESS_API_KEY
Regulations.gov — AI documents and comment deadlines: credential required: REGULATIONS_API_KEY
SAM.gov — AI procurement notices: credential required: SAM_API_KEY
Source cadence and retrieval status
Source
Cadence
Last success
Next due
Current state
OpenAI official news
30 min
28 Sep, 14:53
28 Sep, 15:23
ok
Anthropic official news
30 min
28 Sep, 14:53
28 Sep, 15:23
ok
Google DeepMind official blog
30 min
28 Sep, 14:53
28 Sep, 15:23
ok
Google Research blog
30 min
28 Sep, 14:53
28 Sep, 15:23
ok
Hugging Face blog
120 min
28 Sep, 14:23
28 Sep, 16:23
ok
NVIDIA technical blog
120 min
28 Sep, 14:23
28 Sep, 16:23
ok
arXiv AI preprints
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
arXiv robotics preprints
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
arXiv machine learning preprints
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
vLLM releases
60 min
28 Sep, 13:53
28 Sep, 14:53
unchanged
llama.cpp releases
60 min
28 Sep, 13:53
28 Sep, 14:53
unchanged
Transformers releases
60 min
28 Sep, 13:54
28 Sep, 14:54
ok
SGLang releases
60 min
28 Sep, 13:53
28 Sep, 14:53
unchanged
Qwen model repositories
60 min
28 Sep, 13:53
28 Sep, 14:53
ok
deepseek-ai model repositories
60 min
28 Sep, 13:53
28 Sep, 14:53
ok
meta-llama model repositories
60 min
28 Sep, 13:53
28 Sep, 14:53
unchanged
Epoch AI — Gradient Updates
120 min
28 Sep, 14:23
28 Sep, 16:23
ok
METR research
120 min
28 Sep, 14:23
28 Sep, 16:23
unchanged
The Innermost Loop
30 min
28 Sep, 14:53
28 Sep, 15:23
ok
Moonshots with Peter Diamandis
30 min
28 Sep, 14:53
28 Sep, 15:23
unchanged
Jack Clark — Import AI
180 min
28 Sep, 12:22
28 Sep, 15:22
ok
arXiv computational linguistics preprints
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
arXiv computer vision preprints
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
arXiv quantitative biology preprints
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
Hugging Face papers
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
Hugging Face recent model repositories
60 min
28 Sep, 13:53
28 Sep, 14:53
ok
Hugging Face recent dataset repositories
120 min
28 Sep, 14:23
28 Sep, 16:23
ok
GitHub trending repositories
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
GitHub trending Python repositories
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
GitHub trending Jupyter repositories
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
OpenRouter newest model listings
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
SWE-bench leaderboard
360 min
28 Sep, 11:52
28 Sep, 17:52
unchanged
Product Hunt AI launches
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
SEC latest EDGAR filings
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
ARPA-E funding opportunities
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
ARPA-H funding opportunities
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
DARPA opportunities
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
FDA press announcements
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
NIST AI publications
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
LessWrong latest posts
360 min
28 Sep, 11:52
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Hacker News newest
360 min
28 Sep, 11:52
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Alignment Forum latest posts
360 min
28 Sep, 11:52
28 Sep, 17:52
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Anthropic careers
360 min
28 Sep, 11:52
28 Sep, 17:52
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Google DeepMind careers
360 min
28 Sep, 11:52
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GitHub topic artificial intelligence
360 min
28 Sep, 11:52
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GitHub topic agents
360 min
28 Sep, 11:52
28 Sep, 17:52
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GitHub topic robotics
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
Hugging Face trending Spaces
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
OpenRouter monthly rankings
360 min
28 Sep, 11:52
28 Sep, 17:52
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Artificial Analysis models
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
FDA AI/ML-enabled medical devices
360 min
28 Sep, 11:52
28 Sep, 17:52
unchanged
NIST AI Resource Center
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
EU AI Office
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
Defense Innovation Unit open solicitations
360 min
28 Sep, 11:52
28 Sep, 17:52
unchanged
DOE EERE funding opportunities
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
AI Engineer events
360 min
28 Sep, 11:52
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ok
Foresight Institute events
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
Copenhagen Institute for Futures Studies
360 min
28 Sep, 11:52
28 Sep, 17:52
unchanged
SynBioBeta
360 min
28 Sep, 11:52
28 Sep, 17:52
unchanged
NeurIPS program site
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
ICML program site
360 min
28 Sep, 11:52
28 Sep, 17:52
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ICLR program site
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
bioRxiv AI-relevant biology preprints
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
medRxiv computational and clinical preprints
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
ClinicalTrials.gov AI studies
360 min
Unknown
28 Sep, 21:47
error · stale
GitHub trending developers
360 min
28 Sep, 11:52
28 Sep, 17:52
ok
Federal Register — artificial intelligence
30 min
28 Sep, 14:53
28 Sep, 15:23
ok
Federal Register — compute, data centers and energy
30 min
28 Sep, 14:53
28 Sep, 15:23
ok
Federal Register — biotechnology and clinical AI
60 min
28 Sep, 13:53
28 Sep, 14:53
ok
Congress — frontier technology bills and actions
60 min
Unknown
28 Sep, 21:47
error · stale
Regulations.gov — AI documents and comment deadlines
60 min
Unknown
28 Sep, 21:47
error · stale
SAM.gov — AI procurement notices
360 min
Unknown
28 Sep, 21:47
error · stale
Early observations
Unverified candidates for review. Ranking is a heuristic, not confidence or probability.
I posted a sloppier version of this essay with nearly identical semantic content earlier tonight, which you can read here . I've replaced that text with this one, which is less enthusiastic but more readable. I don't think any of the early comments' content is invalidated by the rewrite, though they may have been responding…
Enzyme kinetic parameters inform metabolic models, yet experimental measurements are sparse. A growing body of work predicts them from protein and substrate features, but software fragmentation hinders adoption, so downstream tools lock into the most accessible method. We present OpenKinetics Predictor (at…
capabilitydeploymentconstraints
bioRxiv preprint; not peer reviewed or clinically validated
Advances in protein structure prediction have enabled all-atom protein-ligand co-folding models that predict bound conformations directly from sequence and small-molecule structure. However, these models often fail to generalize to novel binding sites or alternative protein conformational states, limiting their utility for…
capabilityconstraintspolicy
bioRxiv preprint; not peer reviewed or clinically validated
{"id": "~deepseek/deepseek-pro-latest", "name": "DeepSeek: DeepSeek Pro Latest", "description": "This model always redirects to the latest model in the DeepSeek Pro family.", "context_length": 1048576, "architecture": {"modality": "text->text", "input_modalities": ["text"], "output_modalities": ["text"], "tokenizer":…
capabilitydeployment
model listing metadata; capabilities/pricing require verification
arXiv:2609.30595v1 Announce Type: new Abstract: Synchronised action annotations are needed to train controllable world models and these datasets remain elusive. Existing approaches make use of instrumented platforms with calibrated sensors, costly manual annotation, or latent-action models which lack grounding. We instead…
arXiv:2609.30709v1 Announce Type: new Abstract: Traffic signal control (TSC) is essential for mitigating urban congestion. Recent advances in vision-language models (VLMs) enable richer interpretation of intersection scenes, opening new opportunities for visual-context-aware TSC. However, the loose coupling and repeated…
arXiv:2609.30741v1 Announce Type: new Abstract: Binocular rendering requires two nearby views of the same scene and therefore repeats substantial visibility and shading work. We present a 2D Gaussian Splatting (2DGS) pipeline that fully renders a dominant-eye RGB image and an alpha-weighted depth proxy, reprojects that image…
arXiv:2609.30769v1 Announce Type: new Abstract: Cross-domain few-shot learning requires adapting a classifier to a new visual domain from very few labelled examples without target-time parameter updates. We isolate one question: under a fixed global representation, what does joint query-support adaptation contribute to…
arXiv:2609.30982v1 Announce Type: new Abstract: Modern AI image generators are increasingly deployed as opaque APIs, where customers can query the deployed service, but cannot inspect model weights or architecture. This creates a practical challenge: a provider may pass governance certification with one generator and later…
arXiv:2609.31005v1 Announce Type: new Abstract: Open-vocabulary 3D maps enable robots to reason about previously unknown environments using natural language. However, existing systems typically segment every incoming image, associate detections with persistent 3D segments, and frequently perform costly Vision-Language (VL)…
arXiv:2609.31028v1 Announce Type: new Abstract: Vision-language models (VLMs) achieve strong zero-shot (ZS) classification on histology images but do not perform as well on cytology, whose stains and cell morphology differ markedly compared to histology. Conditional random fields (CRFs) can refine noisy VLM predictions by…
capabilitydeploymentconstraints
preprint; not peer reviewed
Reviewed developments
Proposed decisions, not executed actions. Breakthrough verification is not yet established.
DECISION PROPOSED · 17 Sep, 08:20
Upgrade llama.cpp before the next Apple Silicon MoE evaluation.
Decision rationale; primary evidence not yet reviewed.
Recorded rationaleThe release fixes a Metal path that can turn large activations into NaNs. Any earlier MoE result on that path may be unreliable.
Reviewed evidenceDecision rationale; primary evidence not yet reviewed.
DECISION PROPOSED · 17 Sep, 08:20
Do not adopt Mimir 1B from parameter count alone.
Decision rationale; primary evidence not yet reviewed.
Recorded rationalellama.cpp reports roughly four times the decode work of an equal-width dense model and about 3 GB of F16 KV cache at 4K context.
Reviewed evidenceDecision rationale; primary evidence not yet reviewed.
DECISION PROPOSED · 17 Sep, 08:20
Treat Groq 3 LPX power-efficiency claims as a future infrastructure signal, not available GCC capacity.
Decision rationale; primary evidence not yet reviewed.
Recorded rationaleThe vendor framing strengthens the case that power per useful token is the bottleneck, but it provides no dated GCC commissioning or customer-access evidence.
Reviewed evidenceDecision rationale; primary evidence not yet reviewed.
Decision queue
Every item has a next move and a condition that can overturn it.
DO NOWDECISION PROPOSED
Upgrade llama.cpp before the next Apple Silicon MoE evaluation.
The release fixes a Metal path that can turn large activations into NaNs. Any earlier MoE result on that path may be unreliable.
Say this to AI implementation teams running local modelsPause comparisons made on the affected Apple Silicon path. Re-run one representative task on the fixed build before treating earlier quality or latency results as decision-grade.
Next movePin a build at or after b10994, rerun one representative MoE prompt, and compare output plus latency with the previous build.
What would change this judgment?
The affected mul_mm_id path was not used by our model or backend configuration.
WATCHDECISION PROPOSED
Do not adopt Mimir 1B from parameter count alone.
llama.cpp reports roughly four times the decode work of an equal-width dense model and about 3 GB of F16 KV cache at 4K context.
Say this to CIOs and private-AI operatorsA small parameter count is not a low operating cost. Require cost per successful task, memory use and supervision time before choosing this model for private workflows.
Next moveWait for prefix-LM support and an independent cost-per-success result before spending evaluation time.
What would change this judgment?
A reproducible task test shows enough accuracy gain to offset the reported memory and decode costs.
WATCHDECISION PROPOSED
Treat Groq 3 LPX power-efficiency claims as a future infrastructure signal, not available GCC capacity.
The vendor framing strengthens the case that power per useful token is the bottleneck, but it provides no dated GCC commissioning or customer-access evidence.
Say this to GCC sovereign, infrastructure and data-center leadersPlan around power per useful AI outcome and verified access dates. Do not count announced silicon as sovereign capacity until an operating deployment exposes customer access and independent performance data.
Next moveTrack independent watts-per-token and customer-access evidence tied to an operating Vera Rubin deployment.
What would change this judgment?
A dated operational deployment exposes customer access and independently measured performance per watt.
WATCHDECISION PROPOSED
Watch Anthropic ART as a research-automation case; do not treat as a validated application.
The described pipeline links parallel genomic search to candidate triage and human lab testing, but ART function remains unknown and independent validation is absent.
Say this to USEK research and AI workflow advisorsTreat this as a workflow signal: agents can search and rank candidates, while human scientists retain experimental validation. Do not infer a usable biological tool or general autonomous discovery from this case.
Next moveReview the technical report and seek independent replication; measure cost, expert review time, candidate yield and repeatability.
What would change this judgment?
The technical report or independent replication fails to confirm the reported RNA expression or novelty, or comparable searches fail to reproduce the candidate workflow.
WATCHDECISION PROPOSED
Watch Ringg's production pattern; do not treat the customer-story performance figures as independently validated.
OpenAI describes task-based model routing, specialist agents, offline evaluation, staged rollout, live endpoint monitoring and human escalation in a deployed multi-channel service workflow.
Say this to MJ's agent workflows, USEK applied research, and GCC service deploymentsFor an agent deployment, pair task routing and specialist steps with offline evaluation, gradual release, endpoint health checks and clear human handoff. Treat the reported resolution, CSAT and savings figures as vendor/customer claims until independently reproduced.
Next moveAsk for independently measured task mix, resolution denominator, escalation rate, language-specific quality, cost per completed task and post-deployment monitoring evidence.
What would change this judgment?
Independent customer or auditor data shows that completion rates, quality, or cost improvements do not generalize beyond selected workloads or fail to include human handling costs.
WATCHDECISION PROPOSED
Track AnewDDE as a research-automation signal; do not recommend adoption from the preprint claim alone.
A bioRxiv preprint describes an agentic closed-loop drug-discovery workflow connecting structure, affinity, design and experiment selection. It reports 10.7% success for single-digit-nanomolar binders in one nanobody campaign; this remains author-reported evidence.
Say this to USEK research automation and MJ agent workflowsPotentially relevant to a bounded literature or lab-workflow review if methods and data substantiate the claim; no deployment decision yet.
Next moveInspect full methods and results, especially campaign denominator, assay protocol, controls, and availability of data/code.
What would change this judgment?
Full methods fail to support the reported binder yield, the result is not reproducible, or performance depends on a selected campaign that does not generalize.
WATCHDECISION PROPOSED
Use claude-opus-5-5 for approved premium Claude work after confirming the exact provider model ID; evaluate task-level quality, time, and spend before broadening its role.
Anthropic announced Opus 5.5 on Sep 22 and claims 40% lower typical token-billed running cost than Opus 5. The official model page gives the API identifier claude-opus-5-5. Its quality and cost claims remain vendor-reported.
Say this to MJ agent workflows and Claude routingPin claude-opus-5-5 for eligible premium tasks only after checking the active provider supports that exact ID; record outcome and measured usage against a fixed task baseline.
Next moveVerify exact provider model ID and run one bounded representative task comparison against the current Opus baseline, recording quality, elapsed time, token use and billed cost.
What would change this judgment?
Provider does not expose the exact model ID, or a task-matched comparison shows worse quality or no worthwhile end-to-end cost/time benefit.
WATCHDECISION PROPOSED
Treat OpenRouter's DeepSeek Latest price/catalog revision as a route-specific cost signal; verify an exact pinned model/version before updating any cost assumption or routing decision.
OpenRouter's current pages map Pro Latest to V4 Pro 0813 at $3.78/M output tokens and Flash Latest to V4.1 Flash at $0.60/M. The prior catalog snapshot differs materially, but latest aliases and slight page/API discrepancies prevent a like-for-like tariff conclusion.
Say this to MJ agent workflows, USEK research, and GCC deployment cost planningBefore relying on a DeepSeek Latest route for cost estimates, pin the exact model version and check the current provider/router tariff against the earlier catalog snapshot. No routing change is proposed from this listing alone.
Next moveCompare the pinned V4 Pro 0813 and V4.1 Flash tariffs with any direct-provider price sheet and calculate cost per successful representative task before changing a budget or route.
What would change this judgment?
The apparent increase disappears when comparing the same pinned model version, or direct provider pricing and a fixed-task cost-per-success measurement show no meaningful change for MJ's workload.
Lead / lag scoreboard
52 matched items. Baseline discoveries are shown but never claimed as wins.
VERIFIED LEAD80h ahead
Introducing MentalHealthBench
Compared with Welcome to September 27, 2026. Prospective timing is measurable.
VERIFIED LEAD80h ahead
Contrastive Language Models
Compared with Welcome to September 27, 2026. Prospective timing is measurable.
VERIFIED LEAD43h ahead
Introducing Astra for Law
Compared with Welcome to September 20, 2026. Prospective timing is measurable.
VERIFIED LEAD43h ahead
Sep 18, 2026 Announcements Partnering with Accenture on embedded evaluation
Compared with Welcome to September 20, 2026. Prospective timing is measurable.
VERIFIED LEAD43h ahead
Human brain is two separate organs, Stanford Medicine-led research finds
Compared with Welcome to September 20, 2026. Prospective timing is measurable.
VERIFIED LEAD43h ahead
If math is more than proof, we need to better celebrate the rest of it
Compared with Welcome to September 20, 2026. Prospective timing is measurable.
Enzyme kinetic parameters inform metabolic models, yet experimental measurements are sparse. A growing body of work predicts them from protein and substrate features, but software fragmentation hinders adoption, so downstream tools lock into the most accessible method. We present OpenKinetics Predictor (at…
capabilitydeploymentconstraints
bioRxiv preprint; not peer reviewed or clinically validated
Advances in protein structure prediction have enabled all-atom protein-ligand co-folding models that predict bound conformations directly from sequence and small-molecule structure. However, these models often fail to generalize to novel binding sites or alternative protein conformational states, limiting their utility for…
capabilityconstraintspolicy
bioRxiv preprint; not peer reviewed or clinically validated
I posted a sloppier version of this essay with nearly identical semantic content earlier tonight, which you can read here . I've replaced that text with this one, which is less enthusiastic but more readable. I don't think any of the early comments' content is invalidated by the rewrite, though they may have been responding…
arXiv:2609.30595v1 Announce Type: new Abstract: Synchronised action annotations are needed to train controllable world models and these datasets remain elusive. Existing approaches make use of instrumented platforms with calibrated sensors, costly manual annotation, or latent-action models which lack grounding. We instead…
arXiv:2609.30709v1 Announce Type: new Abstract: Traffic signal control (TSC) is essential for mitigating urban congestion. Recent advances in vision-language models (VLMs) enable richer interpretation of intersection scenes, opening new opportunities for visual-context-aware TSC. However, the loose coupling and repeated…
arXiv:2609.30741v1 Announce Type: new Abstract: Binocular rendering requires two nearby views of the same scene and therefore repeats substantial visibility and shading work. We present a 2D Gaussian Splatting (2DGS) pipeline that fully renders a dominant-eye RGB image and an alpha-weighted depth proxy, reprojects that image…
arXiv:2609.30769v1 Announce Type: new Abstract: Cross-domain few-shot learning requires adapting a classifier to a new visual domain from very few labelled examples without target-time parameter updates. We isolate one question: under a fixed global representation, what does joint query-support adaptation contribute to…
arXiv:2609.30982v1 Announce Type: new Abstract: Modern AI image generators are increasingly deployed as opaque APIs, where customers can query the deployed service, but cannot inspect model weights or architecture. This creates a practical challenge: a provider may pass governance certification with one generator and later…
arXiv:2609.31005v1 Announce Type: new Abstract: Open-vocabulary 3D maps enable robots to reason about previously unknown environments using natural language. However, existing systems typically segment every incoming image, associate detections with persistent 3D segments, and frequently perform costly Vision-Language (VL)…
arXiv:2609.31028v1 Announce Type: new Abstract: Vision-language models (VLMs) achieve strong zero-shot (ZS) classification on histology images but do not perform as well on cytology, whose stains and cell morphology differ markedly compared to histology. Conditional random fields (CRFs) can refine noisy VLM predictions by…
arXiv:2609.31050v1 Announce Type: new Abstract: Efficient video generation requires reducing the quadratic cost of self-attention over long spatio-temporal token sequences. Existing efficient-attention methods typically apply the same computation pattern to every token, even though denoising difficulty varies substantially…
arXiv:2609.31135v1 Announce Type: new Abstract: Spatio-Temporal Video Grounding (STVG) aims to localize the spatio-temporal tube in a video corresponding to a natural language query. While recent methods achieve strong performance in fully supervised, weakly supervised, and zero-shot settings, they typically rely on…
capabilitydeploymentconstraints
preprint; not peer reviewed
Hypothesis register
Amber means the prerequisite still lacks reviewed evidence.
agent-reliability8 days overdue
When can agents complete our multi-step work with fewer interventions?
Reliable extended task completion4 reviewed
Lower human correction time1 reviewed
Independent task reproduction0 reviewed
Next discriminating observationIndependent fixed-task results reporting failures, retries and human minutes
open-model-economics8 days overdue
When do deployable open models become viable for our private workflows?
Usable license and released weights1 reviewed
Fits available memory1 reviewed
Acceptable quality at fully loaded cost1 reviewed
Next discriminating observationA reproducible cost-per-success comparison under our hardware constraints
gcc-compute-bottlenecks8 days overdue
Does announced sovereign compute translate into usable capacity?
Delivered equipment0 reviewed
Commissioned power1 reviewed
Accessible operational service0 reviewed
Next discriminating observationDated commissioning and customer-access evidence, not another capacity pledge
research-automation8 days overdue
Which scientific workflows now produce independently validated results?
Reliable execution0 reviewed
Affordable validated result0 reviewed
Experimental access2 reviewed
Independent scientific validation0 reviewed
Repeat adoption0 reviewed
Next discriminating observationIndependent replication including total cost and expert verification time
eval-credibility8 days overdue
Which frontier capability claims survive independent evaluation and provenance scrutiny?
Evaluator independence disclosed0 reviewed
Task and harness equivalence established0 reviewed
Independent reproduction0 reviewed
Contamination and privileged-access risks addressed0 reviewed
Next discriminating observationA primary evaluation artifact and an independent reproduction using the same task definition
This page is a decision surface, not a feed reader. “Decision proposed” records an advisory recommendation; it does not prove execution. Repeated coverage does not count as independent evidence. Unknown measurements remain unknown. Email inventory is incomplete; this page does not represent a complete account inventory.