2 citations · 2 across the 6 of their papers we have counts for
7 papers
Wiring Matters: Injection Topology and Initialization of Affordance Heads in Vision-Language-Action Policies
Zijian An, Linhan Wang, Jiayan Wang +4
Dense affordance supervision is an appealing auxiliary signal for vision-language-action (VLA) policies, yet naively co-training an affordance head can severely damage instruction…
ROG-Grasp: Root-Oriented Geometry for Robotic Grasping and Placement
Zijian An, Augustus Sroka, Ran Yang +8
Orientation-aware manipulation is essential in post-harvest agricultural processing, where produce must be grasped and placed in consistent configurations. This paper presents ROG-…
VILAS: A VLA-Integrated Low-cost Architecture with Soft Grasping for Robotic Manipulation
Zijian An, Hadi Khezam, Bill Cai +5
We present VILAS, a fully low-cost, modular robotic manipulation platform designed to support end-to-end vision-language-action (VLA) policy learning and deployment on accessible h…
TPO: Uncertainty-Guided Exploration Control for Stable Multi-Turn Agentic Reinforcement Learning
Haixin Wang, Hejie Cui, Chenwei Zhang +7
Recent progress in multi-turn reinforcement learning (RL) has significantly improved reasoning LLMs' performances on complex interactive tasks. Despite advances in stabilization te…
WebCoach: Self-Evolving Web Agents with Cross-Session Memory Guidance
Genglin Liu, Shijie Geng, Sha Li +4
Multimodal LLM-powered agents have recently demonstrated impressive capabilities in web navigation, enabling agents to complete complex browsing tasks across diverse domains. Howev…
FullStack Bench: Evaluating LLMs as Full Stack Coders
Bytedance-Seed-Foundation-Code-Team, :, Yao Cheng +53
As the capabilities of code large language models (LLMs) continue to expand, their applications across diverse code intelligence domains are rapidly increasing. However, most exist…
InfiBench: Evaluating the Question-Answering Capabilities of Code Large Language Models
Linyi Li, Shijie Geng, Zhenwen Li +7
Large Language Models for code (code LLMs) have witnessed tremendous progress in recent years. With the rapid development of code LLMs, many popular evaluation benchmarks, such as…