collaborators

8 papers

cs.CL2026

TurnGuide: Enhancing Meaningful Full Duplex Spoken Interactions via Dynamic Turn-Level Text-Speech Interleaving

Wenqian Cui, Lei Zhu, Xiaohui Li +4

Full-Duplex Speech Language Models (FD-SLMs) are specialized foundation models designed to enable natural, real-time spoken interactions by modeling complex conversational turn-tak…

cs.AI2026

Benchmark Everything Everywhere All at Once

Shiyun Xiong, Dongming Wu, Peiwen Sun +5

Benchmarks are fundamental for evaluating and advancing LLMs and MLLMs by providing standardized and explicit measures of performance. However, their construction is labor-intensiv…

cs.LG2026

Memorize Theorems, Not Instances: Probing SFT Generalization through Mathematical Reasoning

Ruiying Peng, Mengyu Yang, Jing Lei +3

Supervised Fine-Tuning (SFT) is widely used for task-specific adaptation, yet recent work shows it systematically undermines reasoning generalization. We argue the root cause is no…

cs.CV2026

Deeper Thought, Weaker Aim: Understanding and Mitigating Perceptual Impairment during Reasoning in Multimodal Large Language Models

Ruiying Peng, Xueyu Wu, Jing Lei +3

Multimodal large language models (MLLMs) often suffer from perceptual impairments under extended reasoning modes, particularly in visual question answering (VQA) tasks. We identify…

cs.CL2026

BitLM: Unlocking Multi-Token Language Generation with Bitwise Continuous Diffusion

Shaobin Zhuang, Yuang Ai, Jiaming Han +7

Autoregressive language models generate text one token at a time, yet natural language is inherently structured in multi-token units, including phrases, n-grams, and collocations t…

cs.CL2026

Minimizing Modality Gap from the Input Side: Your Speech LLM Can Be a Prosody-Aware Text LLM

Wenqian Cui, Xiao-Hui Li, Daxin Tan +2

Speech large language models (SLMs) are typically built from text large language model (TLM) checkpoints, yet they still suffer from a substantial modality gap. Prior work has main…