3 citations · 9 across the 15 of their papers we have counts for
16 papers
IA-RAG: Interval-Algebra-Driven Temporal Reasoning for Dynamic Knowledge Retrieval
Xiaoman Wang, Yaoze Zhang, Wenzhuo Fan +7
Retrieval-Augmented Generation (RAG) has shown strong effectiveness in grounding Large Language Models (LLMs) with external knowledge. However, existing RAG and Graph RAG framework…
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…
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…
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…
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…
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…
Investigating Redundancy in Multimodal Large Language Models with Multiple Vision Encoders
Yizhou Wang, Song Mao, Yang Chen +8
Recent multimodal large language models (MLLMs) increasingly integrate multiple vision encoders to improve performance on various benchmarks, assuming that diverse pretraining obje…
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…
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…
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…
DocGenome: An Open Large-scale Scientific Document Benchmark for Training and Testing Multi-modal Large Language Models
Renqiu Xia, Song Mao, Xiangchao Yan +19
Scientific documents record research findings and valuable human knowledge, comprising a vast corpus of high-quality data. Leveraging multi-modality data extracted from these docum…
LimSim++: A Closed-Loop Platform for Deploying Multimodal LLMs in Autonomous Driving
Daocheng Fu, Wenjie Lei, Licheng Wen +5
The emergence of Multimodal Large Language Models ((M)LLMs) has ushered in new avenues in artificial intelligence, particularly for autonomous driving by offering enhanced understa…
TrafficMCTS: A Closed-Loop Traffic Flow Generation Framework with Group-Based Monte Carlo Tree Search
Ze Fu, Licheng Wen, Pinlong Cai +3
Traffic flow simulation within the domain of intelligent transportation systems is garnering significant attention, and generating realistic, diverse, and human-like traffic patter…
LimSim: A Long-term Interactive Multi-scenario Traffic Simulator
Licheng Wen, Daocheng Fu, Song Mao +4
With the growing popularity of digital twin and autonomous driving in transportation, the demand for simulation systems capable of generating high-fidelity and reliable scenarios i…
Human-like Decision-making at Unsignalized Intersection using Social Value Orientation
Yan Tong, Licheng Wen, Pinlong Cai +3
With the commercial application of automated vehicles (AVs), the sharing of roads between AVs and human-driven vehicles (HVs) becomes a common occurrence in the future. While resea…
Bringing Diversity to Autonomous Vehicles: An Interpretable Multi-vehicle Decision-making and Planning Framework
Licheng Wen, Pinlong Cai, Daocheng Fu +2
With the development of autonomous driving, it is becoming increasingly common for autonomous vehicles (AVs) and human-driven vehicles (HVs) to travel on the same roads. Existing s…