Bug Reproduction Tests as Signals for Code Agents
How code agents can use bug reproduction tests as diagnostic signals during patch generation, not just post-hoc checks.
Signals, research, and debates around general intelligence and superintelligence.
Hub content is updated incrementally.
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.
Why lossy memory can be more dangerous than no memory, and what it means for long-term memory design in LLM agents.
A survey reframes continual learning for industrial LLMs as a closed-loop update and release operations problem.
A study on stealth assessment of financial literacy using game logs, multi-agent LLMs, and BKT, with focus on label quality.
A 2026 arXiv paper proposes randomized repeated calls to stabilize black-box AI, with tradeoffs in cost and sigma range.
Prob-BBDM shows promising MRI sequence translation, but 2D limits, 3D consistency, and safety validation matter.