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20242026
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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

CoME: Empowering Channel-of-Mobile-Experts with Informative Hybrid-Capabilities Reasoning

Yuxuan Liu, Weikai Xu, Kun Huang +9

Mobile Agents can autonomously execute user instructions, which requires hybrid-capabilities reasoning, including screen summary, subtask planning, action decision and action funct…

cs.CL2026

MobileBench-OL: A Comprehensive Chinese Benchmark for Evaluating Mobile GUI Agents in Real-World Environment

Qinzhuo Wu, Zhizhuo Yang, Hanhao Li +3

Recent advances in mobile Graphical User Interface (GUI) agents highlight the growing need for comprehensive evaluation benchmarks. While new online benchmarks offer more realistic…

cs.CL2025

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.CL2025

BacktrackAgent: Enhancing GUI Agent with Error Detection and Backtracking Mechanism

Qinzhuo Wu, Pengzhi Gao, Wei Liu +1

Graphical User Interface (GUI) agents have gained substantial attention due to their impressive capabilities to complete tasks through multiple interactions within GUI environments…

cs.CL2025

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…

cs.CL2025

Mobile-Bench-v2: A More Realistic and Comprehensive Benchmark for VLM-based Mobile Agents

Weikai Xu, Zhizheng Jiang, Yuxuan Liu +7

VLM-based mobile agents are increasingly popular due to their capabilities to interact with smartphone GUIs and XML-structured texts and to complete daily tasks. However, existing…