5 citations · 6 across the 6 of their papers we have counts for
6 papers
Paritok-4B: Intent-Conditioned Context Compression for Coding Agents
Jiayu Shi, Luzhuo Chen
Coding agents re-send large file reads and tool outputs to a frontier LLM every turn, and this context dominates their token bill. General-purpose prompt compressors are trained on…
An Empirical Cost Attribution of Context-Compression Gateways in Multi-Turn Coding Agents
Luzhuo Chen, Jiayu Shi
Context compression is widely proposed as a way to cut the token bill of LLM coding agents, and public benchmarks report that aggressive compression preserves task-solving quality.…
Robobench: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models as Embodied Brain
Yulin Luo, Chun-Kai Fan, Menghang Dong +19
Building robots that can perceive, reason, and act in dynamic, unstructured environments remains a central challenge. Recent embodied systems often follow a dual-system paradigm, w…
RoboBrain 2.0 Technical Report
BAAI RoboBrain Team, Mingyu Cao, Huajie Tan +50
We introduce RoboBrain 2.0, our latest generation of embodied vision-language foundation models, designed to unify perception, reasoning, and planning for complex embodied tasks in…
RoboBrain: A Unified Brain Model for Robotic Manipulation from Abstract to Concrete
Yuheng Ji, Huajie Tan, Jiayu Shi +14
Recent advancements in Multimodal Large Language Models (MLLMs) have shown remarkable capabilities across various multimodal contexts. However, their application in robotic scenari…
Semi-supervised Skin Detection by Network with Mutual Guidance
Yi He, Jiayuan Shi, Chuan Wang +5
In this paper we present a new data-driven method for robust skin detection from a single human portrait image. Unlike previous methods, we incorporate human body as a weak semanti…