3 papers
cs.LG2026
QuantLRM: Quantization of Large Reasoning Models via Fine-Tuning Signals
Nan Zhang, Eugene Kwek, Yusen Zhang +4
Weight-only quantization is important for compressing Large Language Models (LLMs). Inspired by the spirit of classical magnitude pruning, we study whether the magnitude of weight…
cs.CL2025
TaxoAdapt: Aligning LLM-Based Multidimensional Taxonomy Construction to Evolving Research Corpora
Priyanka Kargupta, Nan Zhang, Yunyi Zhang +3
The rapid evolution of scientific fields introduces challenges in organizing and retrieving scientific literature. While expert-curated taxonomies have traditionally addressed this…
cs.CL2024
SiReRAG: Indexing Similar and Related Information for Multihop Reasoning
Nan Zhang, Prafulla Kumar Choubey, Alexander Fabbri +5
Indexing is an important step towards strong performance in retrieval-augmented generation (RAG) systems. However, existing methods organize data based on either semantic similarit…