HuggingFace
HumanCLAW: Can Vision-Language Models Act Through a Body?
Evaluating whether a vision-language model (VLM) can act through a physical body is challenging. The outcome of an ac...
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HuggingFace
TurboVLA: Real-Time Vision-Language-Action Model at 32 Hz on an RTX 4090 with <1 GB VRAM
Vision-language-action (VLA) models commonly adopt an LLM-centric V to L to A pathway, where visual observations are ...
HuggingFace
Can AI agents conduct open-ended AI research? Early evidence from two case studies
Forecasts of explosive AI progress hinge on AI agents automating AI research. But evidence on whether agents can carr...
HuggingFace
OmegaUse-OfficeVal: Benchmarking LLM Agents on Long-Horizon Office-Suite Tasks with Economic Grounding
Large language model (LLM) agents are increasingly expected to assist users in completing tasks. However, existing be...
HuggingFace
StealthBench: Measuring Operational Stealth in Autonomous Offensive-Security Agents
Stealth, the discipline of achieving an objective without revealing your presence, capabilities, or collected intelli...
HuggingFace
CAST: Game Solvers as Turn-Level Teachers for LLM Agents
Training large language models (LLMs) to act in long-horizon games is a promising step toward generalist decision-mak...
HuggingFace
DecoEvo: Score-Decoupled Co-Evolution of Solver and Rubric-Generator Skills in Text Space
Text-space optimization adapts large language models (LLMs) by editing external natural-language artifacts rather tha...
HuggingFace
SkillRise: Agentic Reinforcement Learning for Cross-Task Skill Evolution
Large language model agents often encounter related yet distinct tasks that share reusable solution patterns. Yet sta...
HuggingFace
CoRT: Counterfactual Replay for Token-Level Rubric-Guided Policy Optimization
Rubric-based reinforcement learning enriches language model training by evaluating model outputs against explicit cri...
HuggingFace
CLBench-V: Evaluating Multimodal Context Learning from Grounding to Knowledge Acquisition
Real-world tasks often require models to learn from task-specific context rather than relying only on pre-trained kno...
HuggingFace
Grading the Narrators: An Isnad-Rijal Framework for Claim-Level Provenance in Multi-Agent Knowledge Systems
Modern multi-agent knowledge systems increasingly accumulate knowledge through chains of autonomous transformations r...
HuggingFace
SecRespond: Benchmarking AI Agents for Real-World Post-Compromise Incident Response
Large Language Model (LLM) agents are increasingly adopted in real-world security operations with access to host arti...