…Existing financial agents remain turn-based and workflow-disposable. We propose InKH, a financial-agent architecture combining: an event-stream view of user/market/tool updates; a bounded working context buffer assembled…
…Step-Aware Online Preference Distillation for Agent Reinforcement Learning (2026) Learn Where Outcomes Diverge: Efficient VLA RL via Probabilistic Chunk Masking (2026) ParaVT: Taming the Tool Prior Paradox for Parallel Tool Use…
…the strongest agent hallucinates 15.1% of its verifiable spatial claims and makes over half of its accusations without grounded evidence. We release the full engine, evaluation framework, toolkit, and logs at…
…Evaluating Proactive Personal Assistant Agents in Long-Horizon Workflows (2026) Latent Preference Modeling for Cross-Session Personalized Tool Calling (2026) KnowU-Bench: Towards Interactive, Proactive, and Personalized Mobile Agent Evaluation (2026) Remember…
This is really cool, would love to play around with this and see if can get running on Mac OS w/ a local MCP server and tool call implementations. Where are the…
…AI-generated summary As AI agents move from chat interfaces to systems that read private data, call tools, and execute multi-step workflows, guardrails become a last line of defense against concrete…
…actions to Exploration , Implementation , Verification , or Orchestration based on trajectory history rather than tool identity alone. On AgentLens-Bench , the quality score separates passing trajectories into Lucky, Solid, and Ideal tiers and…
…Generated by Qwen/Qwen2.5-Coder-32B-Instruct Tool retrieval over large API catalog s is a core bottleneck for LLM agents: user queries arrive in colloquial, often underspecified language, while the…
…Evaluating Agent Creative Reasoning via Affordance-Based Tool Repurposing (2026) From Where Things Are to What They Are For: Benchmarking Spatial-Functional Intelligence in Multimodal LLMs (2026) MemEye: A Visual-Centric Evaluation…
…View arXiv page View PDF Project page GitHub 2 Add to collection Community DAR introduces an agentic setup where LLMs query statutes on demand through tools rather than receiving all rules in…