5 citations · 9 across the 7 of their papers we have counts for
7 papers
MSME: A Multi-Stage Multi-Expert Framework for Zero-Shot Stance Detection
Yuanshuo Zhang, Aohua Li, Bo Chen +2
LLM-based approaches have recently achieved impressive results in zero-shot stance detection. However, they still struggle in complex real-world scenarios, where stance understandi…
Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-Correction
Yong Lin, Shange Tang, Bohan Lyu +17
We introduce Goedel-Prover-V2, a series of open-source language models that set a new state-of-the-art in automated theorem proving. Built on the standard expert iteration and rein…
Streamlining Biomedical Research with Specialized LLMs
Linqing Chen, Weilei Wang, Yubin Xia +30
In this paper, we propose a novel system that integrates state-of-the-art, domain-specific large language models with advanced information retrieval techniques to deliver comprehen…
SAPPHIRE: Preconditioned Stochastic Variance Reduction for Faster Large-Scale Statistical Learning
Jingruo Sun, Zachary Frangella, Madeleine Udell
Regularized empirical risk minimization (rERM) has become important in data-intensive fields such as genomics and advertising, with stochastic gradient methods typically used to so…
Wait-Less Offline Tuning and Re-solving for Online Decision Making
Jingruo Sun, Wenzhi Gao, Ellen Vitercik +1
Online linear programming (OLP) has found broad applications in revenue management and resource allocation. State-of-the-art OLP algorithms achieve low regret by repeatedly solving…
PharmaGPT: Domain-Specific Large Language Models for Bio-Pharmaceutical and Chemistry
Linqing Chen, Weilei Wang, Zilong Bai +33
Large language models (LLMs) have revolutionized Natural Language Processing (NLP) by minimizing the need for complex feature engineering. However, the application of LLMs in speci…
PatentGPT: A Large Language Model for Intellectual Property
Zilong Bai, Ruiji Zhang, Linqing Chen +24
In recent years, large language models(LLMs) have attracted significant attention due to their exceptional performance across a multitude of natural language process tasks, and hav…