3 papers
cs.CL2024
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…
cs.AI2024
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Large Language Models (LLMs) exhibit substantial capabilities yet encounter challenges, including hallucination, outdated knowledge, and untraceable reasoning processes.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-…
cs.CL2024
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…