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20232026
most citedDiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models

39 citations · 126 across the 47 of their papers we have counts for

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Showing 2025Show all

16 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.CV2025

SymDrive: Realistic and Controllable Driving Simulator via Symmetric Auto-regressive Online Restoration

Zhiyuan Liu, Daocheng Fu, Pinlong Cai +5

High-fidelity and controllable 3D simulation is essential for addressing the long-tail data scarcity in Autonomous Driving (AD), yet existing methods struggle to simultaneously ach…

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.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.IR2025

HetaRAG: Hybrid Deep Retrieval-Augmented Generation across Heterogeneous Data Stores

Guohang Yan, Yue Zhang, Pinlong Cai +7

Retrieval-augmented generation (RAG) has become a dominant paradigm for mitigating knowledge hallucination and staleness in large language models (LLMs) while preserving data secur…

cs.CL2025

DeepWriter: A Fact-Grounded Multimodal Writing Assistant Based On Offline Knowledge Base

Song Mao, Lejun Cheng, Pinlong Cai +3

Large Language Models (LLMs) have demonstrated remarkable capabilities in various applications. However, their use as writing assistants in specialized domains like finance, medici…

cs.CL2025

From Ranking to Selection: A Simple but Efficient Dynamic Passage Selector for Retrieval Augmented Generation

Siyuan Meng, Junming Liu, Yirong Chen +5

Retrieval-augmented generation (RAG) systems are often bottlenecked by their reranking modules, which typically score passages independently and select a fixed Top-K size. This app…

cs.AI2025

LeanRAG: Knowledge-Graph-Based Generation with Semantic Aggregation and Hierarchical Retrieval

Yaoze Zhang, Rong Wu, Pinlong Cai +5

Retrieval-Augmented Generation (RAG) plays a crucial role in grounding Large Language Models by leveraging external knowledge, whereas the effectiveness is often compromised by the…

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

O-Searcher: A Searching-based Agent Model for Open-Domain Open-Ended Question Answering

Jianbiao Mei, Tao Hu, Daocheng Fu +11

Large Language Models (LLMs), despite their advancements, are fundamentally limited by their static parametric knowledge, hindering performance on tasks requiring open-domain up-to…

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.IR2025★ 2 cited

RAKG:Document-level Retrieval Augmented Knowledge Graph Construction

Hairong Zhang, Jiaheng Si, Guohang Yan +5

With the rise of knowledge graph based retrieval-augmented generation (RAG) techniques such as GraphRAG and Pike-RAG, the role of knowledge graphs in enhancing the reasoning capabi…

cs.CV2025

Aligning Vision to Language: Annotation-Free Multimodal Knowledge Graph Construction for Enhanced LLMs Reasoning

Junming Liu, Siyuan Meng, Yanting Gao +7

Multimodal reasoning in Large Language Models (LLMs) struggles with incomplete knowledge and hallucination artifacts, challenges that textual Knowledge Graphs (KGs) only partially…

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…