1 citations · 2 across the 6 of their papers we have counts for
8 papers
To Think or Not to Think: Pre-Decisional Reasoning Budgets for Referring Audio-Visual Segmentation
Haojie Hu, Senda Chen, Ying Shen +1
Multimodal reasoning systems increasingly assume that longer chain-of-thought (CoT) uniformly improves downstream grounding. We show that this assumption fails in referring audio-v…
RaysUp: Ultra-light Universal Feature Upsampling via Geometry-Aware Ray Representation
Yuchuan Ding, Linfei Li, Lin Zhang +1
Pre-trained Vision Foundation Models (VFMs) have become central to modern computer vision due to their powerful semantic representations and strong generalization ability. However,…
RealVLG-R1: A Large-Scale Real-World Visual-Language Grounding Benchmark for Robotic Perception and Manipulation
Linfei Li, Lin Zhang, Ying Shen
Visual-language grounding aims to establish semantic correspondences between natural language and visual entities, enabling models to accurately identify and localize target object…
ES-MemEval: Benchmarking Conversational Agents on Personalized Long-Term Emotional Support
Tiantian Chen, Jiaqi Lu, Ying Shen +1
Large Language Models (LLMs) have shown strong potential as conversational agents. Yet, their effectiveness remains limited by deficiencies in robust long-term memory, particularly…
Representing Sounds as Neural Amplitude Fields: A Benchmark of Coordinate-MLPs and A Fourier Kolmogorov-Arnold Framework
Linfei Li, Lin Zhang, Zhong Wang +3
Although Coordinate-MLP-based implicit neural representations have excelled in representing radiance fields, 3D shapes, and images, their application to audio signals remains under…
SmartSplat: Feature-Smart Gaussians for Scalable Compression of Ultra-High-Resolution Images
Linfei Li, Lin Zhang, Zhong Wang +1
Recent advances in generative AI have accelerated the production of ultra-high-resolution visual content, posing significant challenges for efficient compression and real-time deco…
INR-Bench: A Unified Benchmark for Implicit Neural Representations in Multi-Domain Regression and Reconstruction
Linfei Li, Fengyi Zhang, Zhong Wang +2
Implicit Neural Representations (INRs) have gained success in various signal processing tasks due to their advantages of continuity and infinite resolution. However, the factors in…
M3HG: Multimodal, Multi-scale, and Multi-type Node Heterogeneous Graph for Emotion Cause Triplet Extraction in Conversations
Qiao Liang, Ying Shen, Tiantian Chen +1
Emotion Cause Triplet Extraction in Multimodal Conversations (MECTEC) has recently gained significant attention in social media analysis, aiming to extract emotion utterances, caus…