2 citations · 3 across the 4 of their papers we have counts for
5 papers
Efficient Multimodal Planning Agent for Visual Question-Answering
Zhuo Chen, Xinyu Geng, Xinyu Wang +4
Visual Question-Answering (VQA) is a challenging multimodal task that requires integrating visual and textual information to generate accurate responses. While multimodal Retrieval…
Benchmarking Multimodal Retrieval Augmented Generation with Dynamic VQA Dataset and Self-adaptive Planning Agent
Yangning Li, Yinghui Li, Xinyu Wang +8
Multimodal Retrieval Augmented Generation (mRAG) plays an important role in mitigating the "hallucination" issue inherent in multimodal large language models (MLLMs). Although prom…
ProductAgent: Benchmarking Conversational Product Search Agent with Asking Clarification Questions
Jingheng Ye, Yong Jiang, Xiaobin Wang +5
This paper introduces the task of product demand clarification within an e-commercial scenario, where the user commences the conversation with ambiguous queries and the task-orient…
Let LLMs Take on the Latest Challenges! A Chinese Dynamic Question Answering Benchmark
Zhikun Xu, Yinghui Li, Ruixue Ding +7
How to better evaluate the capabilities of Large Language Models (LLMs) is the focal point and hot topic in current LLMs research. Previous work has noted that due to the extremely…
Towards Real-World Writing Assistance: A Chinese Character Checking Benchmark with Faked and Misspelled Characters
Yinghui Li, Zishan Xu, Shaoshen Chen +7
Writing assistance is an application closely related to human life and is also a fundamental Natural Language Processing (NLP) research field. Its aim is to improve the correctness…