256 citations · 261 across the 16 of their papers we have counts for
17 papers
MuseCritic: Learning Multi-Aspect Song Rewards through Natural-Language Aesthetic Critiques
Jiabao Zhuang, Changhao Jiang, Hanchen Wang +11
Long-form song generation models continue to improve in duration, structural coherence, and acoustic complexity, increasing the need for reliable aesthetic rewards aligned with hum…
EntangleCodec: A Unified Discrete Audio Tokenizer via Semantic-Acoustic Entanglement
Hui Li, Yangfan Gao, Junlin Shang +4
Audio tokenizers serve as the discrete interface between continuous audio and Audio Language Models (ALMs), but existing tokenizers often struggle to support both understanding and…
FRoM-W1: Towards General Humanoid Whole-Body Control with Language Instructions
Peng Li, Zihan Zhuang, Yangfan Gao +16
Humanoid robots are capable of performing various actions such as greeting, dancing and even backflipping. However, these motions are often hard-coded or specifically trained, whic…
OpenNovelty: An LLM-powered Agentic System for Verifiable Scholarly Novelty Assessment
Ming Zhang, Kexin Tan, Yueyuan Huang +20
Evaluating novelty is critical yet challenging in peer review, as reviewers must assess submissions against a vast, rapidly evolving literature. This report presents OpenNovelty, a…
Muse: Towards Reproducible Long-Form Song Generation with Fine-Grained Style Control
Changhao Jiang, Jiahao Chen, Zhenghao Xiang +14
Recent commercial systems such as Suno demonstrate strong capabilities in long-form song generation, while academic research remains largely non-reproducible due to the lack of pub…
From Scores to Preferences: Redefining MOS Benchmarking for Speech Quality Reward Modeling
Yifei Cao, Changhao Jiang, Jiabao Zhuang +11
Assessing the perceptual quality of synthetic speech is crucial for guiding the development and refinement of speech generation models. However, it has traditionally relied on huma…
CMDAR: A Chinese Multi-scene Dynamic Audio Reasoning Benchmark with Diverse Challenges
Hui Li, Changhao Jiang, Hongyu Wang +11
The ability to reason from audio, including speech, environmental sounds, and music, is essential for AI agents to interact effectively in real-world scenarios. Existing benchmarks…
Feedback-Driven Tool-Use Improvements in Large Language Models via Automated Build Environments
Junjie Ye, Changhao Jiang, Zhengyin Du +8
Effective tool use is essential for large language models (LLMs) to interact with their environment. However, progress is limited by the lack of efficient reinforcement learning (R…
LLMEval-Fair: A Large-Scale Longitudinal Study on Robust and Fair Evaluation of Large Language Models
Ming Zhang, Yujiong Shen, Jingyi Deng +19
Existing evaluation of Large Language Models (LLMs) on static benchmarks is vulnerable to data contamination and leaderboard overfitting, critical issues that obscure true model ca…
SpeechRole: A Large-Scale Dataset and Benchmark for Evaluating Speech Role-Playing Agents
Changhao Jiang, Jiajun Sun, Yifei Cao +15
Speech is essential for realistic role-playing, yet existing work on role-playing agents largely centers on text, leaving Speech Role-Playing Agents (SRPAs) underexplored and witho…
What Makes a Good Speech Tokenizer for LLM-Centric Speech Generation? A Systematic Study
Xiaoran Fan, Zhichao Sun, Yangfan Gao +19
Speech-language models (SLMs) offer a promising path toward unifying speech and text understanding and generation. However, challenges remain in achieving effective cross-modal ali…
LLMEval-Med: A Real-world Clinical Benchmark for Medical LLMs with Physician Validation
Ming Zhang, Yujiong Shen, Zelin Li +13
Evaluating large language models (LLMs) in medicine is crucial because medical applications require high accuracy with little room for error. Current medical benchmarks have three…
Game-RL: Synthesizing Multimodal Verifiable Game Data to Boost VLMs' General Reasoning
Jingqi Tong, Jixin Tang, Hangcheng Li +21
Vision-language reinforcement learning (RL) has primarily focused on narrow domains (e.g. geometry or chart reasoning). This leaves broader training scenarios and resources underex…
PFDial: A Structured Dialogue Instruction Fine-tuning Method Based on UML Flowcharts
Ming Zhang, Yuhui Wang, Yujiong Shen +16
Process-driven dialogue systems, which operate under strict predefined process constraints, are essential in customer service and equipment maintenance scenarios. Although Large La…
Beyond Scaling: Measuring and Predicting the Upper Bound of Knowledge Retention in Language Model Pre-Training
Changhao Jiang, Ming Zhang, Yifei Cao +12
The GPT-4 technical report suggests that downstream performance can be predicted from pre-training signals, but offers little methodological detail on how to quantify this. This wo…
MouSi: Poly-Visual-Expert Vision-Language Models
Xiaoran Fan, Tao Ji, Changhao Jiang +21
Current large vision-language models (VLMs) often encounter challenges such as insufficient capabilities of a single visual component and excessively long visual tokens. These issu…
The Rise and Potential of Large Language Model Based Agents: A Survey
Zhiheng Xi, Wenxiang Chen, Xin Guo +26
For a long time, humanity has pursued artificial intelligence (AI) equivalent to or surpassing the human level, with AI agents considered a promising vehicle for this pursuit. AI a…