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20,463 papers
RSI-Opt is introduced, a plug-and-play Recursive Self-Improvement Optimizer Agents which evolves the knowledge that guides this process: a prompt, a playbook of procedures, a library of tested optimizer code, and a decision cadence.
BARC-Bench is introduced, a collection of 110 tasks across nine simulated workspace environments where benign requests leave openings for unsafe actions, and four frontier model configurations are evaluated, highlighting an asymmetric operational risk.
A boundary condition for text-derived multimodal enrichment is suggested: when the relevant task constraints are already available in the textual instruction, synthetic multimodal augmentation may not provide measurable benefit over structured reasoning on the same text.
LLM agents are increasingly deployed in collaborative settings where they pursue separate tasks while sharing resources and operating under review or oversight processes. Such settings create safety risks not only when agents are malicious, but also when they are simply trying to help. Prior work has largely studied ad...
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This work presents an offline evaluation harness for a production conversational agent that stays reproducible despite the live data it operates on changing, and that can be regenerated on demand once it goes stale.
This work introduces a repeated, multi-party, multi-issue negotiation framework in which recurring agents participate in a sequence of negotiation games while one participant covertly attempts to prevent agreement.
An automated red-teaming framework is introduced that formalizes multi-turn jailbreaking as a finite-horizon Markov Decision Process (MDP) without relying on predefined risk taxonomy, providing a scalable and principled framework for multi-turn red-teaming and safety evaluation.
It is found that student-induced histories paired with teacher-generated action prefixes generally provide the strongest standalone training signal, whereas following the student at both levels generally performs worst, and fully on-policy data becomes beneficial when incorporated into a mixture with other configuratio...
A finite conformance study that checks checkpoint state, permission to dispatch, evidence of an external effect and permission to reconcile are distinct obligations through histories scored against a provider effect ledger hidden from the recovering application.
The agent-driven design flow and the resulting division of labor between human and agent is described, taking a step toward a"text-to-ASIC"future for designing RF/mmWave hardware.
Self-Direction is introduced, a mechanism for agents to learn from mistakes that combines the benefits of temporary in-context retries and policy updates and reduces repeated mistakes across future encounters of a task, nearly doubling the reliability of an agent's corrections.
PaperFormalizer, a Lean-based agentic pipeline that helps authors find and close small gaps in their own papers and turn each paper into a Lean-verified version, aims to make research that rests on mathematical proofs more robust.
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.
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