collaborators

14 papers

cs.CL2026

AdaPlanBench: Evaluating Adaptive Planning in Large Language Model Agents under World and User Constraints

Jiayu Liu, Cheng Qian, Zhenhailong Wang +10

Planning for real-world problems by language models often involves both world and user constraints, which may not be fully specified upfront and are progressively disclosed through…

cs.LG2026

Step-Level Sparse Autoencoder for Reasoning Process Interpretation

Xuan Yang, Jiayu Liu, Yuhang Lai +3

Large Language Models (LLMs) have achieved strong complex reasoning capabilities through Chain-of-Thought (CoT) reasoning. However, their reasoning patterns remain too complicated…

cs.AI2026

CostBench: Evaluating Multi-Turn Cost-Optimal Planning and Adaptation in Dynamic Environments for LLM Tool-Use Agents

Jiayu Liu, Cheng Qian, Zhaochen Su +4

Current evaluations of Large Language Model (LLM) agents primarily emphasize task completion, often overlooking resource efficiency and adaptability. This neglects a crucial capabi…

cs.AI2026

PlanBench-XL: Evaluating Long-Horizon Planning of LLM Tool-Use Agents in Large-Scale Tool Ecosystems

Jiayu Liu, Qihan Lin, Cheng Qian +8

LLM agents increasingly operate in large tool ecosystems, where real-world tasks require discovering relevant tools, inferring implicit sub-goals, and adapting to dynamic environme…

cs.AI2026

BioInsight: Multi-Agent Orchestration for Interactive Biomedical Knowledge Discovery

Jieyi Wang, Bingxuan Li, Nanyi Jiang +9

Biomedical deep-research systems increasingly retrieve and synthesize scientific evidence, but their outputs typically collapse heterogeneous evidence into static text, making prov…

cs.AI2026

Brick-Composer: Using MLLMs for Assembly with Diverse Bricks

Jiateng Liu, Bingxuan Li, Zhenhailong Wang +8

We dream of AI agents that can read arbitrary designs and construct real-world objects from reusable building blocks. As a first step toward this vision, we study whether multimoda…