3 citations · 4 across the 14 of their papers we have counts for
14 papers
Beyond Monolingual Deep Research: Evaluating Agents and Retrievers with Cross-Lingual BrowseComp-Plus
Yuheng Lu, Qingcheng Zeng, Heli Qi +6
Deep research agents are increasingly evaluated on their ability to search for evidence, reason over retrieved sources, and produce grounded answers. Existing browsing benchmarks,…
Unified Audio Generation and Editing via Joint Condition Modeling and Progressive Training
Haocheng Dong, Yuheng Lu, Cheng Gong +3
With the growing focus on audio in multimedia applications, numerous advanced works on audio generation have emerged. Existing studies typically treat text-to-audio (TTA) and other…
Separate First, Fuse Later: Mitigating Cross-Modal Interference in Audio-Visual LLMs Reasoning with Modality-Specific Chain-of-Thought
Xuanchen Li, Yuheng Lu, Chenrui Cui +6
Audio and vision provide complementary evidence for audio-visual question answering, yet current audio-visual large language models may suffer from cross-modal interference: inform…
Evaluating the Expressive Appropriateness of Speech in Rich Contexts
Tianrui Wang, Ziyang Ma, Yizhou Peng +26
Evaluating expressive speech remains challenging, as existing methods mainly assess emotional intensity and overlook whether a speech sample is expressively appropriate for its con…
Code-Switching Information Retrieval: Benchmarks, Analysis, and the Limits of Current Retrievers
Qingcheng Zeng, Yuheng Lu, Zeqi Zhou +6
Code-switching is a pervasive linguistic phenomenon in global communication, yet modern information retrieval systems remain predominantly designed for, and evaluated within, monol…
TCM-Eval: An Expert-Level Dynamic and Extensible Benchmark for Traditional Chinese Medicine
Zihao Cheng, Yuheng Lu, Huaiqian Ye +10
Large Language Models (LLMs) have demonstrated remarkable capabilities in modern medicine, yet their application in Traditional Chinese Medicine (TCM) remains severely limited by t…
Perturbation Self-Supervised Representations for Cross-Lingual Emotion TTS: Stage-Wise Modeling of Emotion and Speaker
Cheng Gong, Chunyu Qiang, Tianrui Wang +7
Cross-lingual emotional text-to-speech (TTS) aims to produce speech in one language that captures the emotion of a speaker from another language while maintaining the target voice'…
TransBench: Breaking Barriers for Transferable Graphical User Interface Agents in Dynamic Digital Environments
Yuheng Lu, Qian Yu, Hongru Wang +7
Graphical User Interface (GUI) agents, which autonomously operate on digital interfaces through natural language instructions, hold transformative potential for accessibility, auto…
Enhancing Complex Instruction Following for Large Language Models with Mixture-of-Contexts Fine-tuning
Yuheng Lu, ZiMeng Bai, Caixia Yuan +2
Large language models (LLMs) exhibit remarkable capabilities in handling natural language tasks; however, they may struggle to consistently follow complex instructions including th…
Efficient Emotion and Speaker Adaptation in LLM-Based TTS via Characteristic-Specific Partial Fine-Tuning
Tianrui Wang, Meng Ge, Cheng Gong +11
While LLM-based TTS models exhibit zero-shot emotion and speaker cloning, their cloning fidelity and pronunciation clarity degrade on unseen domains. Fine-tuning is essential for a…
Controlled Low-Rank Adaptation with Subspace Regularization for Continued Training on Large Language Models
Yuheng Lu, Bingshuo Qian, Caixia Yuan +2
Large language models (LLMs) exhibit remarkable capabilities in natural language processing but face catastrophic forgetting when learning new tasks, where adaptation to a new doma…
Expressive Prompting: Improving Emotion Intensity and Speaker Consistency in Zero-Shot TTS
Haoyu Wang, Chunyu Qiang, Tianrui Wang +6
Recent advancements in speech synthesis have enabled large language model (LLM)-based systems to perform zero-shot generation with controllable content, timbre, speaker identity, a…
Graph Neural Netwrok with Interaction Pattern for Group Recommendation
Bojie Wang, Yuheng Lu
With the development of social platforms, people are more and more inclined to combine into groups to participate in some activities, so group recommendation has gradually become a…
Graph Inference Representation: Learning Graph Positional Embeddings with Anchor Path Encoding
Yuheng Lu, Jinpeng Chen, ChuXiong Sun +1
Learning node representations that incorporate information from graph structure benefits wide range of tasks on graph. The majority of existing graph neural networks (GNNs) have li…