5 citations · 12 across the 5 of their papers we have counts for
5 papers
II-Bench: An Image Implication Understanding Benchmark for Multimodal Large Language Models
Ziqiang Liu, Feiteng Fang, Xi Feng +23
The rapid advancements in the development of multimodal large language models (MLLMs) have consistently led to new breakthroughs on various benchmarks. In response, numerous challe…
Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training
Feiteng Fang, Yuelin Bai, Shiwen Ni +3
Large Language Models (LLMs) exhibit substantial capabilities yet encounter challenges, including hallucination, outdated knowledge, and untraceable reasoning processes. Retrieval-…
Open-SQL Framework: Enhancing Text-to-SQL on Open-source Large Language Models
Xiaojun Chen, Tianle Wang, Tianhao Qiu +2
Despite the success of large language models (LLMs) in Text-to-SQL tasks, open-source LLMs encounter challenges in contextual understanding and response coherence. To tackle these…
MoZIP: A Multilingual Benchmark to Evaluate Large Language Models in Intellectual Property
Shiwen Ni, Minghuan Tan, Yuelin Bai +9
Large language models (LLMs) have demonstrated impressive performance in various natural language processing (NLP) tasks. However, there is limited understanding of how well LLMs p…
Leveraging Long and Short-term Information in Content-aware Movie Recommendation
Wei Zhao, Haixia Chai, Benyou Wang +4
Movie recommendation systems provide users with ranked lists of movies based on individual's preferences and constraints. Two types of models are commonly used to generate ranking…