activity
20242026
collaborators

8 papers

eess.AS2026

StepAudio 2.5 Technical Report

Bin Lin, Bo Zhao, Boyong Wu +98

Unified audio-language modeling has emerged as a prominent trend in modern speech systems, promising to bring the reasoning capabilities of large language models to auditory tasks.…

cs.LG2026

DISCOVER: A Solver for Distributional Counterfactual Explanations

Yikai Gu, Lele Cao, Bo Zhao +2

Counterfactual explanations (CE) explain model decisions by identifying input modifications that lead to different predictions. Most existing methods operate at the instance level.…

cs.AI2026

OpAgent: Operator Agent for Web Navigation

Yuyu Guo, Wenjie Yang, Siyuan Yang +12

To fulfill user instructions, autonomous web agents must contend with the inherent complexity and volatile nature of real-world websites. Conventional paradigms predominantly rely…

cs.CL2025

MiroMind-M1: An Open-Source Advancement in Mathematical Reasoning via Context-Aware Multi-Stage Policy Optimization

Xingxuan Li, Yao Xiao, Dianwen Ng +15

Large language models have recently evolved from fluent text generation to advanced reasoning across diverse domains, giving rise to reasoning language models. Among these domains,…

cs.AI2025

Agent4S: The Transformation of Research Paradigms from the Perspective of Large Language Models

Boyuan Zheng, Zerui Fang, Zhe Xu +13

While AI for Science (AI4S) serves as an analytical tool in the current research paradigm, it doesn't solve its core inefficiency. We propose "Agent for Science" (Agent4S)-the use…

cs.CV2025

Task-Related Token Compression in Multimodal Large Language Models from an Explainability Perspective

Lei Lei, Jie Gu, Xiaokang Ma +3

Existing Multimodal Large Language Models (MLLMs) process a large number of visual tokens, leading to significant computational costs and inefficiency. Instruction-related visual t…

cs.CL2024

FuxiTranyu: A Multilingual Large Language Model Trained with Balanced Data

Haoran Sun, Renren Jin, Shaoyang Xu +10

Large language models (LLMs) have demonstrated prowess in a wide range of tasks. However, many LLMs exhibit significant performance discrepancies between high- and low-resource lan…

cs.CL2024

RAAMove: A Corpus for Analyzing Moves in Research Article Abstracts

Hongzheng Li, Ruojin Wang, Ge Shi +7

Move structures have been studied in English for Specific Purposes (ESP) and English for Academic Purposes (EAP) for decades. However, there are few move annotation corpora for Res…