4 papers
DHI: Leveraging Diverse Hallucination Induction for Enhanced Contrastive Factuality Control in Large Language Models
Jiani Guo, Xiangke Zeng, Jie Wu +1
Large language models (LLMs) frequently produce inaccurate or fabricated information, known as "hallucinations," which compromises their reliability. Existing approaches often trai…
SongSage: A Large Musical Language Model with Lyric Generative Pre-training
Jiani Guo, Jiajia Li, Jie Wu +3
Large language models have achieved significant success in various domains, yet their understanding of lyric-centric knowledge has not been fully explored. In this work, we first i…
ToM: Leveraging Tree-oriented MapReduce for Long-Context Reasoning in Large Language Models
Jiani Guo, Zuchao Li, Jie Wu +5
Large Language Models (LLMs), constrained by limited context windows, often face significant performance degradation when reasoning over long contexts. To address this, Retrieval-A…
Teaching Your Models to Understand Code via Focal Preference Alignment
Jie Wu, Haoling Li, Xin Zhang +8
Preference learning extends the performance of Code LLMs beyond traditional supervised fine-tuning by leveraging relative quality comparisons. In existing approaches, a set of n ca…