Automating Agent Safety Testing With Evidence-Based Verification
A summary of arXiv 2607.01793 on automating agent safety testing from risk discovery to evidence-grounded verification.
Signals, research, and debates around general intelligence and superintelligence.
Hub content is updated incrementally.
A summary of arXiv 2607.01793 on automating agent safety testing from risk discovery to evidence-grounded verification.
A paper on combining RLVR with human demonstrations to train style, structure, and diversity beyond verifiable rewards.
How CoAx exposes backup circuits that single ablation can miss due to self-repair in transformers.
A look at RL research using latent space to generate counterfactual feedback in StarCraft II and its coaching potential.
Reviewing where AI and quantum information already deliver practical gains, and why quantum ML advantage still needs caution.
How code agents can use bug reproduction tests as diagnostic signals during patch generation, not just post-hoc checks.
From steering vectors to model calibrators, this paper frames latent-space intervention as a path to better LLM control and trust.
Official data on AI and automation exposure compares office jobs and skilled trades by task structure and employment outlook.
A look at high-risk AI oversight through the humans-as-handlers approach, focusing on intervention, accountability, and trust.
Examines whether AI eliminates jobs or redesigns tasks, and why this shift matters for hiring, reskilling, and productivity.
Public-sector AI disclosures can look compliant yet fail users if they lack meaningful, actionable information.
A curated link roundup from recently collected official updates and tech news.
How to assess whether AI firms' calls for regulation signal safety commitments, competitive strategy, or both.
CoIn links 2D inpainting and 3DGS to reduce reliance on precise multiview masks in 3D scene editing workflows.
A curated link roundup from recently collected official updates and tech news.
How prompt-level NVC constraints shift LLM safety from toxicity blocking to de-escalation quality, with key tradeoffs.
OpenFinGym shifts financial AI evaluation from single-task accuracy to workflow-level testing across prediction, trading, and risk.
Physical AI commercialization depends less on demos than on chip supply, CoWoS packaging, and deployment infrastructure.
Examines whether government early access and company-gated previews are turning AI model launches into a de facto permit system.
AI investment news should be read through official verbs and numbers, not AGI narratives. Build, explore, and assess matter.
Examines the Blind Trust Problem in video reasoning and a reliability-based strategy for frame and tool selection.
How RAG mixes past and current facts, causing stale-fact errors, and why temporal validity matters in retrieval.
Why AI's growth benefits and existential risks should be compared within one economic framework, not separate debates.
Why GUI agents should hand control to users on sensitive screens, beyond task success alone.