Governing Agentic AI Beyond Outputs and Into Actions
Why agentic AI governance must cover autonomy, tool use, external actions, audit logs, and human oversight.
Humanoids, autonomy, and embodied AI.
Hub content is updated incrementally.
Why agentic AI governance must cover autonomy, tool use, external actions, audit logs, and human oversight.
HIVE evaluates how vision-language hallucinations propagate into later reasoning and distort downstream predictions.
An overview of PCBWorld, a KiCad-based environment for evaluating PCB routing AI with native actions and DRC feedback.
Examines whether reusable skill files improve quality, auditability, and operations in repetitive AI data science tasks.
VASP Agent targets reliable scientific automation by combining input consistency, long-run supervision, and output validation.
Why backend evaluation should prioritize SSOT consistency and catching critical PR-stage defects over raw code generation.
Examines how conversational AI and games compete for attention, highlighting different user needs and social dynamics.
A curated link roundup from recently collected official updates and tech news.
Examines whether individual parameters in sparse transformers carry stable meanings amid polysemantic behavior.
Applying LLMs to SSH research requires checking multilingual corpora, knowledge graphs, evaluation, bias, and governance together.
Why next-generation LLM competition is defined by base-model transition, disclosure scope, and product rollout speed.
Examines how limits on models and features in free vs paid AI can shape practice, feedback speed, and project scope.
Why text-driven tool calls make AI agent delegation a structural security issue, backed by refusal-rate evidence.
Why agent safety must verify execution, tool use, and state changes, not just final responses.
A curated link roundup from recently collected official updates and tech news.
Examines how attention-limited pairwise labels in RLHF can distort reward learning and be mistaken for true preference.
A look at training small models to find first reasoning errors, use structured feedback, and revise answers in physics tasks.
Why long-video AI struggles with narrative and causal links, and how hierarchical memory and agentic reasoning help.
Explains why better LLM performance and office automation do not directly reduce electricity, rent, or food costs.
A study examines how LLMs' emotion interpretation consistency can weaken under semantic stress in affective dialogue.
Question-based AI speeds research, but answer accuracy and source verification remain critical for reliable work.
Why agent memory may need to shift from text logs to object-centric executable environment models for long tasks.
Examines how LLM safety alignment can over-refuse legitimate cyber defense requests and reduce utility.
A look at SNR-adaptive unified diffusion for medical segmentation, focusing on label conflicts over headline gains.