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20242026
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cs.CL2026

RouteLMT: Learned Sample Routing for Hybrid LLM Translation Deployment

Yingfeng Luo, Hongyu Liu, Dingyang Lin +6

Large Language Models (LLMs) have achieved remarkable performance in Machine Translation (MT), but deploying them at scale remains prohibitively expensive. A widely adopted remedy…

cs.CL2026

NiuTrans.LMT: Toward Inclusive and Scalable Multilingual Machine Translation with LLMs

Yingfeng Luo, Ziqiang Xu, Yuxuan Ouyang +9

Large language models have significantly advanced Multilingual Machine Translation (MMT), yet scaling to many languages while keeping quality robust across directions remains chall…

cs.CL2026

On the Emotion Understanding of Synthesized Speech

Yuan Ge, Haishu Zhao, Aokai Hao +10

Emotion is a core paralinguistic feature in voice interaction. It is widely believed that emotion understanding models learn fundamental representations that transfer to synthesize…

cs.CL2026

Causal Autoregressive Diffusion Language Model

Junhao Ruan, Bei Li, Yongjing Yin +6

In this work, we propose Causal Autoregressive Diffusion (CARD), a novel framework that unifies the training efficiency of ARMs with the high-throughput inference of diffusion mode…

cs.CL2026

GRAM: A Generative Foundation Reward Model for Reward Generalization

Chenglong Wang, Yang Gan, Yifu Huo +8

In aligning large language models (LLMs), reward models have played an important role, but are standardly trained as discriminative models and rely only on labeled human preference…

cs.CL2025

Probing Preference Representations: A Multi-Dimensional Evaluation and Analysis Method for Reward Models

Chenglong Wang, Yifu Huo, Yang Gan +10

Previous methods evaluate reward models by testing them on a fixed pairwise ranking test set, but they typically do not provide performance information on each preference dimension…