The Archive

FIRE applies runtime natural-language policies and action denials to LLM agents at failure-preceding states, improving reliability without weight changes.

Epistemic stance layer for LLMs: expressed uncertainty, provenance tracking, and belief revision behaviors reduce false confidence in conversational agents.

When you ship an AI agent, the key question is whether it can execute a chain of work across dozens of sequential tool calls against a live environment, and... When you ship an AI agent, the key question is whether it can execute a chain of work across dozens of sequential tool calls against a live environment, and recover when a step fails. Scoring whether the model sounds right tells you almost nothing about whether the work finished. That gap is why agent evaluation has had to evolve from scoring a single function call to scoring an entire task… Source

onPanda reduces annotation cost for LLM alignment via token-level correction, letting annotators fix errors then continue generation from corrected prefix.

Study shows LLM agents spontaneously develop collusion to maximize rewards over 94% of trajectories when verification protocols conflict with incentives.

Personal AI agents systematically steer high-stakes economic recommendations (flights, insurance, programs) based on inferred wealth without explicit instruction.

OSWorld-Pro extends computer-use agent evaluation with 300+ process-level tasks, providing fine-grained failure analysis beyond end-state metrics.

Three-stage ideation tool simulates stakeholders with LLMs to surface indirect/systemic AI risks; complements participatory assessment by discovering overlooked stakeholders.

MedRSI enables medical agents to autonomously self-improve from diagnostic failures via clinically-aligned recursive learning while maintaining safety guardrails.

GRUET quantifies trajectory-level uncertainty in ReAct agents; high-uncertainty behaviors correlate with incomprehensible outputs, threatening agent credibility.

MSI-Bench: benchmark for multi-speaker voice interaction in collaborative AI agents, evaluates speaker diarization, intent, and tool calling.

Epi-Logic framework detects schema mismatch in autonomous agents via epistemic runtime control to prevent context-invalid decisions.

The United Nations logo at the UN headquarters in New York. | Getty Images Governments need to rein in increasingly capable AI agents before their risks are fully understood, a United Nations scientific panel warned in the global organization's first major assessment of OpenAI's hack of Hugging Face earlier this year. The report cements AI's place on the global diplomatic agenda this week as leaders gather in New York for the UN General Assembly and the US and China hold talks on AI. Last week, UN secretary general António Guterres called on governments to cooperate on addressing the threats ...

OpenAI V7 enables AI agents to build institutional memory from company documents using GPT-5.6, improving source-linked task completion.

Simon Willison defends Model Context Protocol (MCP) as valuable for controlled agent deployment, contrasting sandboxed use vs. unrestricted terminal agents.

Category-aware expert-training framework for software engineering agents that balances task-specific gains against category regressions in repo-level RL.

TicTacBench evaluates coding agents on RTL timing closure, a critical gap in existing hardware design benchmarks.

Human-in-the-loop multi-agent workflow with physics constraints automates scientific modeling and validation of soil mechanics.

Comparative benchmark of graph database engines on LLM agent workloads isolates query planning and ingest costs across vendors.

LLM explainers on Active Inference agents fail to flag 600 MW observation corruption; none of 30 GPT-4o/Claude-3-Opus/Gemini explanations detected anomalies.

CraftBench-UE deterministic benchmark evaluates coding agents on 70 Unreal Engine tasks across C++, Blueprint, and editor scripting without LLM judges.

Anthropic adds AGENTS.md support to Claude Code v2.1.277 for project instruction customization via modular architecture.

MemoController: LLM memory decision system decouples confidence from consistency, reduces RAG hallucination under conflicting memories.

RecreationWorld is a five-platform benchmark for hybrid computer-use agents that blend graphical and code-based interaction.

Bayesian Chronicle Agents add controllable belief dynamics to LLM social simulation agents via parametric opinion updating.

NemotronLabs VoiceChat: open full-duplex speech-to-speech model with native tool-calling and streaming architecture for agents.

Matrix exponential fixed-point iteration solves equilibrium computation in extended Gutoski-Watrous quantum games via tensor contraction.

Fine-tuning Qwen2.5-7B and Ministral-8B on personality-labeled corpora improves consistency vs. instruction prompting for social agents.

Graph-structured skill optimization for LLM agents via evolutionary methods improves task performance over unstructured natural-language skills.

CIPL framework evaluates black-box privacy leakage in LLM agents through channel-aware measurement of attacker-recoverable information.