2 citations · 2 across the 7 of their papers we have counts for
7 papers
LLM Agents Are Latent Context Managers: Eliciting Self-Managed Context via State Proprioception
Binyan Xu, Haitao Li, Kehuan Zhang
Long-horizon tool agents are bottlenecked by how their context grows toward the limits of the context window. Recent systems make context management agent- or system-controlled, bu…
From Multi-Agent to Single-Agent: When Is Skill Distillation Beneficial?
Binyan Xu, Dong Fang, Haitao Li +1
Multi-agent systems (MAS) for structured data-science tasks externalize analytical control through workflows spanning stages, tools, shared state, verification, and repair. Distill…
APEX-SQL: Talking to the data via Agentic Exploration for Text-to-SQL
Bowen Cao, Weibin Liao, Yushi Sun +3
Text-to-SQL systems powered by Large Language Models have excelled on academic benchmarks but struggle in complex enterprise environments. The primary limitation lies in their reli…
Kimi K2.5: Visual Agentic Intelligence
Kimi Team, Tongtong Bai, Yifan Bai +333
We introduce Kimi K2.5, an open-source multimodal agentic model designed to advance general agentic intelligence. K2.5 emphasizes the joint optimization of text and vision so that…
OpenReward: Learning to Reward Long-form Agentic Tasks via Reinforcement Learning
Ziyou Hu, Zhengliang Shi, Minghang Zhu +5
Reward models (RMs) have become essential for aligning large language models (LLMs), serving as scalable proxies for human evaluation in both training and inference. However, exist…
Enhancing LLM-Based Agents via Global Planning and Hierarchical Execution
Junjie Chen, Haitao Li, Jingli Yang +2
Intelligent agent systems based on Large Language Models (LLMs) have shown great potential in real-world applications. However, existing agent frameworks still face critical limita…