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

collaborators
Showing 2025Show all

11 papers · 1 filter

cs.CV2025

UR-Bench: A Benchmark for Multi-Hop Reasoning over Ultra-High-Resolution Images

Siqi Li, Xinyu Cai, Jianbiao Mei +7

Recent multimodal large language models (MLLMs) show strong capabilities in visual-language reasoning, yet their performance on ultra-high-resolution imagery remains largely unexpl…

cs.AI2025

MemVerse: Multimodal Memory for Lifelong Learning Agents

Junming Liu, Yifei Sun, Weihua Cheng +11

Despite rapid progress in large-scale language and vision models, AI agents still suffer from a fundamental limitation: they cannot remember. Without reliable memory, agents catast…

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.CV2025

Vision-Centric 4D Occupancy Forecasting and Planning via Implicit Residual World Models

Jianbiao Mei, Yu Yang, Xuemeng Yang +4

End-to-end autonomous driving systems increasingly rely on vision-centric world models to understand and predict their environment. However, a common ineffectiveness in these model…

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.CV2025

IWR-Bench: Can LVLMs reconstruct interactive webpage from a user interaction video?

Yang Chen, Minghao Liu, Yufan Shen +18

The webpage-to-code task requires models to understand visual representations of webpages and generate corresponding code. However, existing benchmarks primarily focus on static sc…

cs.CV2025

OmniCaptioner: One Captioner to Rule Them All

Yiting Lu, Jiakang Yuan, Zhen Li +17

We propose OmniCaptioner, a versatile visual captioning framework for generating fine-grained textual descriptions across a wide variety of visual domains. Unlike prior methods lim…

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…

cs.RO2025

LimSim Series: An Autonomous Driving Simulation Platform for Validation and Enhancement

Daocheng Fu, Naiting Zhong, Xu Han +5

Closed-loop simulation environments play a crucial role in the validation and enhancement of autonomous driving systems (ADS). However, certain challenges warrant significant atten…