activity
20192026
most citedDiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models

39 citations · 104 across the 32 of their papers we have counts for

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Showing cs.CLShow all

5 papers · 1 filter

cs.CL2025

RE-Searcher: Robust Agentic Search with Goal-oriented Planning and Self-reflection

Daocheng Fu, Jianbiao Mei, Licheng Wen +11

Large language models (LLMs) excel at knowledge-intensive question answering and reasoning, yet their real-world deployment remains constrained by knowledge cutoff, hallucination,…

cs.CL2025

Learning on the Job: An Experience-Driven Self-Evolving Agent for Long-Horizon Tasks

Cheng Yang, Xuemeng Yang, Licheng Wen +9

Large Language Models have demonstrated remarkable capabilities across diverse domains, yet significant challenges persist when deploying them as AI agents for real-world long-hori…

cs.CL2025

EvolveR: Self-Evolving LLM Agents through an Experience-Driven Lifecycle

Rong Wu, Xiaoman Wang, Jianbiao Mei +8

Current Large Language Model (LLM) agents show strong performance in tool use, but lack the crucial capability to systematically learn from their own experiences. While existing fr…

cs.CL2025

KG-TRACES: Enhancing Large Language Models with Knowledge Graph-constrained Trajectory Reasoning and Attribution Supervision

Rong Wu, Pinlong Cai, Jianbiao Mei +5

Large language models (LLMs) have made remarkable strides in various natural language processing tasks, but their performance on complex reasoning problems remains hindered by a la…

cs.CL2025

GDI-Bench: A Benchmark for General Document Intelligence with Vision and Reasoning Decoupling

Siqi Li, Yufan Shen, Xiangnan Chen +13

The rapid advancement of multimodal large language models (MLLMs) has profoundly impacted the document domain, creating a wide array of application scenarios. This progress highlig…