… The following papers were recommended by the Semantic Scholar API Beyond Binary Correctness: Scaling Evaluation of Long-Horizon Agents on Subjective Enterprise Tasks 2026 Claw-Eval: Towards Trustworthy Evaluation of Autonomous Agents 2026 AlphaEval: Evaluating Agents in Production 2026 ClawBench: C… …
… But real medical-AI research is a workflow, and failures are often hidden inside that workflow. ❕The solution: AutoMedBench provides the workflow-aware evaluation of LLM agents in AutoResearch tasks, and covering wild range of tasks from segmentation, image enhancement, VQA, report generation and l… …
… Systematic Enumeration and Coverage Audit of LLM Agent Tool Call Safety 2026 Emergent Strategic Reasoning Risks in AI: A Taxonomy-Driven Evaluation Framework 2026 CritBench: A Framework for Evaluating Cybersecurity Capabilities of Large Language Models in IEC 61850 Digital Substation Environments 2… …
… Even advanced AI agents function on message exchange formats, successively exchanging messages with users, systems, with itself i.e. chain-of-thought and tools in a single stream of computation. …
… The following papers were recommended by the Semantic Scholar API HATS: Hardness-Aware Trajectory Synthesis for GUI Agents 2026 WebCompass: Towards Multimodal Web Coding Evaluation for Code Language Models 2026 GameWorld: Towards Standardized and Verifiable Evaluation of Multimodal Game Agents 2026… …
… The following papers were recommended by the Semantic Scholar API Mitigating Provenance-Role Collapse in Long-Term Agents via Typed Memory Representation 2026 MemGuard: Preventing Memory Contamination in Long-Term Memory-Augmented Large Language Models 2026 MemFail: Stress-Testing Failure Modes of … …
… I found the explanation of Hugging Face’s “Skills Training” initiative — how it lets you use a coding‑agent like Claude Code or other supported agents to fine‑tune large language models, submit GPU jobs, monitor progress and push trained models to the Hub — particularly eye‑opening. …