activity
20242026
most citedInternLM2 Technical Report

29 citations · 43 across the 29 of their papers we have counts for

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Showing cs.AIShow all

5 papers · 1 filter

cs.AI2026

FACET: Preserving Source Intent and Executable State in Terminal Task Synthesis

Kou Shi, Zun Wang, Qisheng Su +10

Training terminal agents requires scalable executable supervision, yet synthesizing high-quality terminal tasks remains challenging. Each task couples an instruction, an initialize…

cs.AI2026

AsyncTool: Evaluating the Asynchronous Function Calling Capability under Multi-Task Scenarios

Kou Shi, Ziao Zhang, Shiting Huang +7

Large language model (LLM)-based agents have shown strong capabilities in using external tools to solve complex tasks. However, existing evaluations often overlook the temporal dim…

cs.AI2026

Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligence

Guanting Dong, Junting Lu, Junjie Huang +17

Large language models are increasingly expected to serve as general-purpose agents that interact with external, stateful tool environments. The Model Context Protocol (MCP) and bro…

cs.AI2026

SkillFlow:Benchmarking Lifelong Skill Discovery and Evolution for Autonomous Agents

Ziao Zhang, Kou Shi, Shiting Huang +13

As the capability frontier of autonomous agents continues to expand, they are increasingly able to complete specialized tasks through plug-and-play external skills. Yet current ben…

cs.AI2025

Agentic Jigsaw Interaction Learning for Enhancing Visual Perception and Reasoning in Vision-Language Models

Yu Zeng, Wenxuan Huang, Shiting Huang +9

Although current large Vision-Language Models (VLMs) have advanced in multimodal understanding and reasoning, their fundamental perceptual and reasoning abilities remain limited. S…