3 papers
cs.CL2025
Training LLMs to be Better Text Embedders through Bidirectional Reconstruction
Chang Su, Dengliang Shi, Siyuan Huang +5
Large language models (LLMs) have increasingly been explored as powerful text embedders. Existing LLM-based text embedding approaches often leverage the embedding of the final toke…
cs.LG2025
HAMMER: Hamiltonian Curiosity Augmented Large Language Model Reinforcement
Ming Yang, Xiaofan Li, Zhiyuan Ma +4
Recent curriculum reinforcement learning for large language models (LLMs) typically rely on difficulty-based annotations for data filtering and ordering. However, such methods suff…
cs.CL2025
Gumbel Reranking: Differentiable End-to-End Reranker Optimization
Siyuan Huang, Zhiyuan Ma, Jintao Du +5
RAG systems rely on rerankers to identify relevant documents. However, fine-tuning these models remains challenging due to the scarcity of annotated query-document pairs. Existing…