1 citations · 1 across the 2 of their papers we have counts for
7 papers · 1 filter
DiCoRe: Enhancing Zero-shot Event Detection via Divergent-Convergent LLM Reasoning
Tanmay Parekh, Kartik Mehta, Ninareh Mehrabi +2
Zero-shot Event Detection (ED), the task of identifying event mentions in natural language text without any training data, is critical for document understanding in specialized dom…
Self-Routing RAG: Binding Selective Retrieval with Knowledge Verbalization
Di Wu, Jia-Chen Gu, Kai-Wei Chang +1
Selective retrieval aims to make retrieval-augmented generation (RAG) more efficient and reliable by skipping retrieval when an LLM's parametric knowledge suffices. Despite promisi…
Magnet: Multi-turn Tool-use Data Synthesis and Distillation via Graph Translation
Fan Yin, Zifeng Wang, I-Hung Hsu +9
Large language models (LLMs) have exhibited the ability to effectively utilize external tools to address user queries. However, their performance may be limited in complex, multi-t…
SNaRe: Domain-aware Data Generation for Low-Resource Event Detection
Tanmay Parekh, Yuxuan Dong, Lucas Bandarkar +4
Event Detection (ED) -- the task of identifying event mentions from natural language text -- is critical for enabling reasoning in highly specialized domains such as biomedicine, l…
Fact or Guesswork? Evaluating Large Language Models' Medical Knowledge with Structured One-Hop Judgments
Jiaxi Li, Yiwei Wang, Kai Zhang +5
Large language models (LLMs) have been widely adopted in various downstream task domains. However, their abilities to directly recall and apply factual medical knowledge remains un…
Control Large Language Models via Divide and Conquer
Bingxuan Li, Yiwei Wang, Tao Meng +2
This paper investigates controllable generation for large language models (LLMs) with prompt-based control, focusing on Lexically Constrained Generation (LCG). We systematically ev…