Category
20,463 papers
Capability-Grounded Agentic Planning (CGAP) is presented, which compiles the tool catalog deterministically into a PDDL model, uses an LLM to turn the request into goals, and solves the model with a classical planner.
When a language-model agent fails a multi-step task, can another model find the decisive mistake and fix it with a single action? We introduce ReplayRCA, a benchmark that scores such diagnoses by intervention rather than by agreement with annotations: the environment is restored to the state preceding the chosen step,...
A pilot expert workshop used to explore violet teaming as a governance methodology for biodefense-relevant AI capabilities and described observations from the exercise, summarizes the workshop design, outputs, and lessons learned.
Noura is presented, which pairs LLM planning with executable personal specifications instantiated from public clinical guidance and individual health and dietary profiles, and turns executed plans and contextually credited revisions into supervision for compact models, recovering targets even from trajectories that nev...
Reach audiences
Advertise in front of researchers, engineers, and readers.
Good decisions often require considering how outcomes will feel. Yet large language models (LLMs) increasingly enter decision workflows, despite little being known about how they map outcomes to feelings or use those mappings in choice. We tested how LLMs anticipated gambling or stock-trading outcomes would feel and wh...
The implemented prototype separates deterministic planning from large language model generation, represents content and delivery parameters explicitly, shapes each script through a four-phase attention taper, validates structural and lexical constraints, performs a bounded error-aware retry, and quarantines unresolved...
P-ContextBench provides measurable targets for improving the accuracy, reliability, and safety of LLM-based personal agents, a realistic, verifiable, and scalable benchmark for evaluating personal-context understanding.
It is observed that models can form statistical estimates of the monitor's effectiveness and use these estimates to guide attempts to evade detection, and highlight the need to evaluate CoT-based oversight under adaptive conditions, where the monitoring process itself may influence the behavior it seeks to observe.
Evaluating agents built on eight recent models, it is found that retrieval improves the Brier score of all eight in every retrieval setting and lifts the leading agents to the market consensus on the 54 questions linked to Polymarket, with the best three scoring slightly above it.
This work investigates the source of an entropy collapse in the first few tokens following the opening thinking tag and exploits this mechanism to recover CoT controllability through two inference-time interventions on initial tokens, finding that the relationship with monitorability depends on the evaluation.
DiRAFT (Discourse Realization from Aggregate First-order Transitions), which extracts financial concept graphs and records the order in which concepts are first introduced, is introduced, which pools adjacent concept transitions across training records and samples new graph plans from aggregate transition, starting-con...
Interactive, read-grounded simulation is established as a practical foundation for safe and scalable agentic test-time scaling in shared, non-resettable environments and reforms next-observation prediction as a multi-turn evidence-acquisition task.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
