1 citations · 1 across the 7 of their papers we have counts for
5 papers · 1 filter
Learning how to Forget: Fine-tuning for Long-Context Sparse Attention
Matthias Seeger, Zeyu Zhang, Vihang Patil +2
A lot of prior work addressed key-value (KV) cache selection and compression by sparse attention to enable long-context inference for transformer language models without excessive…
Beyond Scale and Generation: Understanding Language Model-based Entity Matching
Zeyu Zhang, Xue Li, Iacer Calixto +2
Entity matching identifies records that refer to the same real-world entity. Language models can be adapted to this task through bi-encoder, cross-encoder, and generative matcher a…
Cost-Efficient RAG for Entity Matching with LLMs: A Blocking-based Batch Processing Framework
Chuangtao Ma, Zeyu Zhang, Arijit Khan +2
Large language models (LLMs) offer a compelling approach to entity matching (EM) in label-scarce settings, yet their matching quality is sensitive to records with ambiguous or spar…
NeuroSymActive: Differentiable Neural-Symbolic Reasoning with Active Exploration for Knowledge Graph Question Answering
Rong Fu, Yang Li, Zeyu Zhang +7
Large pretrained language models and neural reasoning systems have advanced many natural language tasks, yet they remain challenged by knowledge-intensive queries that require prec…
MetaToolAgent: Towards Generalizable Tool Usage in LLMs through Meta-Learning
Zheng Fang, Wolfgang Mayer, Zeyu Zhang +4
Tool learning is increasingly important for large language models (LLMs) to effectively coordinate and utilize a diverse set of tools in order to solve complex real-world tasks. By…