247 citations · 316 across the 24 of their papers we have counts for
6 papers · 1 filter
Understanding the Role of LLMs in Multimodal Evaluation Benchmarks
Botian Jiang, Lei Li, Xiaonan Li +5
The rapid advancement of Multimodal Large Language Models (MLLMs) has been accompanied by the development of various benchmarks to evaluate their capabilities. However, the true na…
Case2Code: Scalable Synthetic Data for Code Generation
Yunfan Shao, Linyang Li, Yichuan Ma +11
Large Language Models (LLMs) have shown outstanding breakthroughs in code generation. Recent work improves code LLMs by training on synthetic data generated by some powerful LLMs,…
Inference-Time Decontamination: Reusing Leaked Benchmarks for Large Language Model Evaluation
Qin Zhu, Qingyuan Cheng, Runyu Peng +5
The training process of large language models (LLMs) often involves varying degrees of test data contamination. Although current LLMs are achieving increasingly better performance…
Scaling Laws for Fact Memorization of Large Language Models
Xingyu Lu, Xiaonan Li, Qinyuan Cheng +3
Fact knowledge memorization is crucial for Large Language Models (LLM) to generate factual and reliable responses. However, the behaviors of LLM fact memorization remain under-expl…
Unified Active Retrieval for Retrieval Augmented Generation
Qinyuan Cheng, Xiaonan Li, Shimin Li +7
In Retrieval-Augmented Generation (RAG), retrieval is not always helpful and applying it to every instruction is sub-optimal. Therefore, determining whether to retrieve is crucial…
Aggregation of Reasoning: A Hierarchical Framework for Enhancing Answer Selection in Large Language Models
Zhangyue Yin, Qiushi Sun, Qipeng Guo +9
Recent advancements in Chain-of-Thought prompting have facilitated significant breakthroughs for Large Language Models (LLMs) in complex reasoning tasks. Current research enhances…