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cs.CL2026

FAB-Bench: A Framework for Adaptive RAG Benchmarking in Semiconductor Manufacturing

Jingbin Qian, Congwen Yi, Min Xia +3

Retrieval-Augmented Generation (RAG) has become critical for knowledge-intensive applications, yet evaluating its performance in vertical domains remains difficult due to domain co…

cs.CL2026

Text as a Universal Interface for Transferable Personalization

Yuting Liu, Jian Guan, Jia-Nan Li +4

We study the problem of personalization in large language models (LLMs). Prior work predominantly represents user preferences as implicit, model-specific vectors or parameters, yie…

cs.CL2025

ReFusion: A Diffusion Large Language Model with Parallel Autoregressive Decoding

Jia-Nan Li, Jian Guan, Wei Wu +1

Autoregressive models (ARMs) are hindered by slow sequential inference. While masked diffusion models (MDMs) offer a parallel alternative, they suffer from critical drawbacks: high…

cs.CL2025

AgentPRM: Process Reward Models for LLM Agents via Step-Wise Promise and Progress

Zhiheng Xi, Chenyang Liao, Guanyu Li +12

Despite rapid development, large language models (LLMs) still encounter challenges in multi-turn decision-making tasks (i.e., agent tasks) like web shopping and browser navigation,…

cs.CL2025

Latent Preference Coding: Aligning Large Language Models via Discrete Latent Codes

Zhuocheng Gong, Jian Guan, Wei Wu +2

Large language models (LLMs) have achieved remarkable success, yet aligning their generations with human preferences remains a critical challenge. Existing approaches to preference…

cs.CL2025

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals

Jia-Nan Li, Jian Guan, Wei Wu +1

Large language models (LLMs) have demonstrated significant success in complex reasoning tasks such as math and coding. In contrast to these tasks where deductive reasoning predomin…