2 citations · 3 across the 7 of their papers we have counts for
7 papers
CREM: Compression-Driven Representation Enhancement for Multimodal Retrieval and Comprehension
Lihao Liu, Yan Wang, Biao Yang +10
Multimodal Large Language Models (MLLMs) have shown remarkable success in comprehension tasks such as visual description and visual question answering. However, their direct applic…
Concise and Sufficient Sub-Sentence Citations for Retrieval-Augmented Generation
Guo Chen, Qiuyuan Li, Qiuxian Li +3
In retrieval-augmented generation (RAG) question answering systems, generating citations for large language model (LLM) outputs enhances verifiability and helps users identify pote…
Chart-HQA: A Benchmark for Hypothetical Question Answering in Charts
Xiangnan Chen, Yuancheng Fang, Qian Xiao +5
Multimodal Large Language Models (MLLMs) have garnered significant attention for their strong visual-semantic understanding. Most existing chart benchmarks evaluate MLLMs' ability…
Tree of Reviews: A Tree-based Dynamic Iterative Retrieval Framework for Multi-hop Question Answering
Li Jiapeng, Liu Runze, Li Yabo +3
Multi-hop question answering is a knowledge-intensive complex problem. Large Language Models (LLMs) use their Chain of Thoughts (CoT) capability to reason complex problems step by…
WikiTableEdit: A Benchmark for Table Editing by Natural Language Instruction
Zheng Li, Xiang Chen, Xiaojun Wan
Tabular data, as a crucial form of data representation, exists in diverse formats on the Web. When confronted with complex and irregular tables, manual modification becomes a labor…
WikiIns: A High-Quality Dataset for Controlled Text Editing by Natural Language Instruction
Xiang Chen, Zheng Li, Xiaojun Wan
Text editing, i.e., the process of modifying or manipulating text, is a crucial step in human writing process. In this paper, we study the problem of controlled text editing by nat…
Evaluating, Understanding, and Improving Constrained Text Generation for Large Language Models
Xiang Chen, Xiaojun Wan
Advancements in natural language generation (NLG) and large language models (LLMs) have led to proficient text generation in various tasks. However, integrating intricate constrain…