智能体生态观察
智能体生态动态速递
追踪 AI 智能体（Agent）生态的模型发布、框架开源、行业落地与安全治理动态。
Co-Evolving Harnesses and Models: On-Policy Correction Helps Weaker Models Catch Up Where Imitation Fails
Agent harnesses (the system prompt, tool set, execution hooks, and context-management scaffolding around a model) are a …
ReMoMask-2: Latent Retrieval-Augmented Masked Motion Generation
Text-to-motion (T2M) generation maps natural language to human joint movements, aiding gaming, VR, and robotics. Retriev…
Environments as Scaffold: Enriching Feedback to Bootstrap Self-Evolving Agents in Long-Horizon Tasks
Large Language Models demonstrate remarkable proficiency in static reasoning, yet training them as autonomous agents thr…
SyncWorld: Visual Calibration Enables World Models as Zero-Shot Simulators
World models are increasingly used as policy-in-the-loop imagination environments, where reliable rollouts require fine-…
SchemeArena: Factorized Stress Testing of Scheming in LLM Agents
We study scheming in LLM agents, in which agents covertly pursue misaligned goals. Our focus is to understand how schemi…
AgentGrad: Intervention-guided Prompt Optimization for Multi Agent Systems
Large language model (LLM)-based multi-agent systems (MAS) achieve strong performance by employing specialized multiple …
Grouped Value Attention: Efficient KV Caching via On-Demand Key Reconstruction
The KV cache is a primary bottleneck for Transformer decoding: its memory footprint and cache-read traffic grow with seq…
PlannerForge: LLM Agents for Scenario-Based Testing of Motion Planners in Autonomous Driving
Ensuring the safety of autonomous driving is a critical challenge. Scenario-based testing is a systematic process used t…
SWE-Bench Pro Verified: A Reliable Benchmark for Software Engineering Agents
SWE-Bench Pro has emerged as a standard benchmark for evaluating software engineering agents on challenging repository-l…
TANGO: Humanoid Navigation in Cluttered Environments with a Whole-Body Vision-Language-Action Model
We study the problem of navigating cluttered indoor environments with a humanoid robot. Unlike conventional methods that…
SAEScientist-Bench: Can AI Agents Conduct Autonomous SAE Interpretability Research?
While research on recursive self-improvement (RSI) has predominantly automated model training pipelines, reliable autono…
Feyospace-v1: How the Cyber Mercury Seven Trained Frontier Cyber Models
Training capable cyber agents is often treated primarily as a problem of model scale, yet open-weight post-training is c…
CosmoH2G: A Hand-to-Gripper Transfer Dataset and Baseline Method for Object Manipulation with Complex Spatial Movements
Transferring human hand demonstrations to robotic grippers has recently emerged as a cost-effective solution for robot l…
Scores Alone Do Not Prove Discovery: The Discovery Certification Protocol for Auditing AI Research Agents
AI research agents combine prior knowledge, public sources, and experimental feedback to produce useful results. The Dis…
MOLE: Detecting Insider Threats in AI Agents
Model misalignment, prompt injection, or operator misuse could lead AI agents operating frontier-lab accounts to exfiltr…
Measuring Language Transfer in Robot Policies: Adding Greek to a Cosmos3 Vision-Language-Action Policy
Robot foundation models are trained and evaluated predominantly in English, and robot demonstration corpora do not exist…
PARSER: Read in Parallel, Reason in Depth for Long-Context LLM Agents
Sequential memory agents process long documents by reading chunks one after another while maintaining a compact memory s…
Agentic Visual Generation: From Generative Models to Agentic Control
Visual generation is evolving from generative models used through a single invocation into agentic control processes tha…
DianShi-RxnDB: A Large-Scale, Fine-Grained Organic Reaction Data Platform Built via a Fully Automated Pipeline for Researchers and AI Agents
High-quality structured organic reaction data are essential for developing artificial intelligence for chemistry (AI4Che…
Deep Persona: A Psychologically Grounded Architecture and Evaluation Framework for Role-Playing Agents and Simulations
Existing approaches to persona simulation with Large Language Models (LLMs) mostly rely on shallow character description…