17 citations · 39 across the 11 of their papers we have counts for
6 papers · 1 filter
CRAT: A Multi-Agent Framework for Causality-Enhanced Reflective and Retrieval-Augmented Translation with Large Language Models
Meiqi Chen, Fandong Meng, Yingxue Zhang +2
Large language models (LLMs) have shown great promise in machine translation, but they still struggle with contextually dependent terms, such as new or domain-specific words. This…
Navigating the Nuances: A Fine-grained Evaluation of Vision-Language Navigation
Zehao Wang, Minye Wu, Yixin Cao +3
This study presents a novel evaluation framework for the Vision-Language Navigation (VLN) task. It aims to diagnose current models for various instruction categories at a finer-gra…
MMLongBench-Doc: Benchmarking Long-context Document Understanding with Visualizations
Yubo Ma, Yuhang Zang, Liangyu Chen +13
Understanding documents with rich layouts and multi-modal components is a long-standing and practical task. Recent Large Vision-Language Models (LVLMs) have made remarkable strides…
CELLO: Causal Evaluation of Large Vision-Language Models
Meiqi Chen, Bo Peng, Yan Zhang +1
Causal reasoning is fundamental to human intelligence and crucial for effective decision-making in real-world environments. Despite recent advancements in large vision-language mod…
Causal Evaluation of Language Models
Sirui Chen, Bo Peng, Meiqi Chen +7
Causal reasoning is viewed as crucial for achieving human-level machine intelligence. Recent advances in language models have expanded the horizons of artificial intelligence acros…
Quantifying and Mitigating Unimodal Biases in Multimodal Large Language Models: A Causal Perspective
Meiqi Chen, Yixin Cao, Yan Zhang +1
Recent advancements in Large Language Models (LLMs) have facilitated the development of Multimodal LLMs (MLLMs). Despite their impressive capabilities, MLLMs often suffer from over…