97 citations · 563 across the 101 of their papers we have counts for
32 papers · 1 filter
FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning
Zhonghua Jiang, Jimin Xu, Shengyu Zhang +5
Federated learning (FL) is a promising technology for data privacy and distributed optimization, but it suffers from data imbalance and heterogeneity among clients. Existing FL met…
Learning to Solve Domain-Specific Calculation Problems with Knowledge-Intensive Programs Generator
Chengyuan Liu, Shihang Wang, Lizhi Qing +4
Domain Large Language Models (LLMs) are developed for domain-specific tasks based on general LLMs. But it still requires professional knowledge to facilitate the expertise for some…
Gold Panning in Vocabulary: An Adaptive Method for Vocabulary Expansion of Domain-Specific LLMs
Chengyuan Liu, Shihang Wang, Lizhi Qing +4
While Large Language Models (LLMs) demonstrate impressive generation abilities, they frequently struggle when it comes to specialized domains due to their limited domain-specific k…
RexUniNLU: Recursive Method with Explicit Schema Instructor for Universal NLU
Chengyuan Liu, Shihang Wang, Fubang Zhao +5
Information Extraction (IE) and Text Classification (CLS) serve as the fundamental pillars of NLU, with both disciplines relying on analyzing input sequences to categorize outputs…
Semantic Alignment for Multimodal Large Language Models
Tao Wu, Mengze Li, Jingyuan Chen +6
Research on Multi-modal Large Language Models (MLLMs) towards the multi-image cross-modal instruction has received increasing attention and made significant progress, particularly…
IntOPE: Off-Policy Evaluation in the Presence of Interference
Yuqi Bai, Ziyu Zhao, Chenxin Lyu +2
Off-Policy Evaluation (OPE) is employed to assess the potential impact of a hypothetical policy using logged contextual bandit feedback, which is crucial in areas such as personali…