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cs.CL2026

Unlocking Speech-Text Compositional Powers: Instruction-Following Speech Language Models without Instruction Tuning

Congrui Du, Yang Zhang, Kaizhi Qian +1

Instruction tuning for speech language models (SLMs) is substantially more challenging than for text-based large language models (LLMs), as it requires learning a new modality and…

cs.CL2026

VISUALSKILL: Multimodal Skills for Computer-Use Agents

Ziyan Jiang, Li An, Yujian Liu +5

Computer-use agents (CUAs) approach human-level performance on standardised benchmarks but still struggle on long-horizon tasks and unseen software. Existing skill libraries addres…

cs.CL2025

ProsodyLM: Uncovering the Emerging Prosody Processing Capabilities in Speech Language Models

Kaizhi Qian, Xulin Fan, Junrui Ni +4

Speech language models refer to language models with speech processing and understanding capabilities. One key desirable capability for speech language models is the ability to cap…

cs.CL2025

PLAY2PROMPT: Zero-shot Tool Instruction Optimization for LLM Agents via Tool Play

Wei Fang, Yang Zhang, Kaizhi Qian +2

Large language models (LLMs) are increasingly integrated with specialized external tools, yet many tasks demand zero-shot tool usage with minimal or noisy documentation. Existing s…

cs.CL2025

A Hierarchical Probabilistic Framework for Incremental Knowledge Tracing in Classroom Settings

Xinyi Gao, Qiucheng Wu, Yang Zhang +4

Knowledge tracing (KT) aims to estimate a student's evolving knowledge state and predict their performance on new exercises based on performance history. Many realistic classroom s…

cs.CL2025

ThinkPrune: Pruning Long Chain-of-Thought of LLMs via Reinforcement Learning

Bairu Hou, Yang Zhang, Jiabao Ji +4

We present ThinkPrune, a simple yet effective method for pruning the thinking length for long-thinking LLMs, which has been found to often produce inefficient and redundant thinkin…