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20242026
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cs.CL2026

PolyAlign: Conditional Human-Distribution Alignment

L. D. M. S. Sai Teja, Ufaq Khan, Sathira Silva +2

Post-training methods such as supervised fine-tuning (SFT) and preference optimization typically align language models toward a single global assistant behavior. While effective fo…

cs.CL2025

Evaluating Large Language Models on Multimodal Chemistry Olympiad Exams

Yiming Cui, Xin Yao, Yuxuan Qin +3

Multimodal scientific reasoning remains a significant challenge for large language models (LLMs), particularly in chemistry, where problem-solving relies on symbolic diagrams, mole…

cs.CL2024

A Static and Dynamic Attention Framework for Multi Turn Dialogue Generation

Wei-Nan Zhang, Yiming Cui, Kaiyan Zhang +4

Recently, research on open domain dialogue systems have attracted extensive interests of academic and industrial researchers. The goal of an open domain dialogue system is to imita…

cs.CL2024

Visualizing attention zones in machine reading comprehension models

Yiming Cui, Wei-Nan Zhang, Ting Liu

The attention mechanism plays an important role in the machine reading comprehension (MRC) model. Here, we describe a pipeline for building an MRC model with a pretrained language…

cs.CL2024

Multilingual Multi-Aspect Explainability Analyses on Machine Reading Comprehension Models

Yiming Cui, Wei-Nan Zhang, Wanxiang Che +3

Achieving human-level performance on some of the Machine Reading Comprehension (MRC) datasets is no longer challenging with the help of powerful Pre-trained Language Models (PLMs).…

cs.CL2024

Self-Evolving GPT: A Lifelong Autonomous Experiential Learner

Jinglong Gao, Xiao Ding, Yiming Cui +4

To improve the performance of large language models (LLMs), researchers have explored providing LLMs with textual task-solving experience via prompts. However, they rely on manual…