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20242026
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cs.CL2026

TRACE: A Self-Evolving Skill Bank for Consistent, Limit-Aware LLM Agents

Wenhao Wu, Menghao Zhang, Xin Wang +3

Reliable deployment of LLM agents in user-facing products depends not on raw task-solving ability but on consistency and limit-awareness: behaving the same way across repeated tria…

cs.CL2026

Reference-Free Post-Training of Open Large Language Models for Multilingual Machine Translation

Chris Han, Pengzhi Gao, Pei Fu +1

We study reference-free post-training for multilingual machine translation with open large language models. Starting from the supervised-finetuned MiLMMT-46-v0.1 models, we apply G…

cs.CL2026

UI-MOPD: Multi-Platform On-Policy Distillation for Unified GUI Agents

Niu Lian, Tongbo Chen, Alan Chen +10

Recent advances in multimodal foundation models and agent systems have driven GUI agents from single-platform task execution toward cross-platform interaction. However, unified mul…

cs.CL2026

Revisiting Entropy in Reinforcement Learning for Large Reasoning Models

Renren Jin, Pengzhi Gao, Yuqi Ren +6

Reinforcement learning with verifiable rewards (RLVR) has emerged as a prominent paradigm for enhancing the reasoning capabilities of large language models (LLMs). However, the ent…

cs.CL2026

ExPosST: Explicit Positioning with Adaptive Masking for LLM-Based Simultaneous Machine Translation

Yuzhe Shang, Pengzhi Gao, Yazheng Yang +4

Large language models (LLMs) have recently demonstrated promising performance in simultaneous machine translation (SimulMT). However, applying decoder-only LLMs to SimulMT introduc…

cs.CL2026

MobileIPL: Enhancing Mobile Agents Thinking Process via Iterative Preference Learning

Kun Huang, Weikai Xu, Yuxuan Liu +6

The Chain of Action-Planning Thoughts (CoaT) paradigm has been shown to improve the reasoning performance of VLM-based mobile agents in GUI tasks. However, the scarcity of diverse…