29 citations · 32 across the 20 of their papers we have counts for
25 papers
Are We Testing Too Much? A Survey of Benchmark Compression for Efficient Evaluation of Large Language Models
Guoming Ling, Yupei Lin, Zhongzhan Huang +5
Benchmarks are essential for evaluating and improving large language models (LLMs). Yet many widely used benchmarks are redundant, making evaluation unnecessarily expensive. Benchm…
Zipbench: Low-Cost Framework for Compressing Comprehensive Benchmarks of Large Language Models
Zhongzhan Huang, Junxin Li, Guoming Ling +3
Comprehensive benchmark suites are essential for improving large language models (LLMs), but many widely used benchmarks are redundant, making evaluation unnecessarily expensive. A…
OutLangSplat: 3D Language Gaussian Splatting for UAV Outdoor Scenes
Xia Yan, He Wu, Yanghui Xu +2
3D Language Gaussian Splatting embeds open-vocabulary language features into 3D Gaussian Splatting, providing an efficient explicit representation for text-driven 3D scene understa…
Test-Time Scaling in Multimodal Foundation Models: A Comprehensive Survey of Generation and Reasoning
Cong Wan, Ying He, Zhongzhan Huang +1
Test-time Scaling (TTS) has emerged as a pivotal research direction for enhancing model performance by dynamically allocating computational resources during inference. Recent advan…
Collaborative Multi-Agent Scripts Generation for Enhancing Imperfect-Information Reasoning in Murder Mystery Games
Keyang Zhong, Junlin Xie, Hefeng Wu +2
Vision-language models (VLMs) have shown impressive capabilities in perceptual tasks, yet they degrade in complex multi-hop reasoning under multiplayer game settings with imperfect…
AtomicVLA: Unlocking the Potential of Atomic Skill Learning in Robots
Likui Zhang, Tao Tang, Zhihao Zhan +9
Recent advances in Visual-Language-Action (VLA) models have shown promising potential for robotic manipulation tasks. However, real-world robotic tasks often involve long-horizon,…
TIBR4D: Tracing-Guided Iterative Boundary Refinement for Efficient 4D Gaussian Segmentation
He Wu, Xia Yan, Yanghui Xu +2
Object-level segmentation in dynamic 4D Gaussian scenes remains challenging due to complex motion, occlusions, and ambiguous boundaries. In this paper, we present an efficient lear…
Neural Chain-of-Thought Search: Searching the Optimal Reasoning Path to Enhance Large Language Models
Guoming Ling, Zhongzhan Huang, Yupei Lin +4
Chain-of-Thought reasoning has significantly enhanced the problem-solving capabilities of Large Language Models. Unfortunately, current models generate reasoning steps sequentially…
Robust Egocentric Referring Video Object Segmentation via Dual-Modal Causal Intervention
Haijing Liu, Zhiyuan Song, Hefeng Wu +3
Egocentric Referring Video Object Segmentation (Ego-RVOS) aims to segment the specific object actively involved in a human action, as described by a language query, within first-pe…
Massive Editing for Large Language Models Based on Dynamic Weight Generation
Wentao Wan, Qiqing Lao, Zhiwei Xie +4
Knowledge Editing (KE) is a field that studies how to modify some knowledge in Large Language Models (LLMs) at a low cost (compared to pre-training). Currently, performing large-sc…
GeoRemover: Removing Objects and Their Causal Visual Artifacts
Zixin Zhu, Haoxiang Li, Xuelu Feng +3
Towards intelligent image editing, object removal should eliminate both the target object and its causal visual artifacts, such as shadows and reflections. However, existing image…
DART: Dual Adaptive Refinement Transfer for Open-Vocabulary Multi-Label Recognition
Haijing Liu, Tao Pu, Hefeng Wu +2
Open-Vocabulary Multi-Label Recognition (OV-MLR) aims to identify multiple seen and unseen object categories within an image, requiring both precise intra-class localization to pin…
RoboPearls: Editable Video Simulation for Robot Manipulation
Tao Tang, Likui Zhang, Youpeng Wen +9
The development of generalist robot manipulation policies has seen significant progress, driven by large-scale demonstration data across diverse environments. However, the high cos…
MiniLongBench: The Low-cost Long Context Understanding Benchmark for Large Language Models
Zhongzhan Huang, Guoming Ling, Shanshan Zhong +2
Long Context Understanding (LCU) is a critical area for exploration in current large language models (LLMs). However, due to the inherently lengthy nature of long-text data, existi…
RoBridge: A Hierarchical Architecture Bridging Cognition and Execution for General Robotic Manipulation
Kaidong Zhang, Rongtao Xu, Pengzhen Ren +4
Operating robots in open-ended scenarios with diverse tasks is a crucial research and application direction in robotics. While recent progress in natural language processing and la…
RouterEval: A Comprehensive Benchmark for Routing LLMs to Explore Model-level Scaling Up in LLMs
Zhongzhan Huang, Guoming Ling, Yupei Lin +4
Routing large language models (LLMs) is a new paradigm that uses a router to recommend the best LLM from a pool of candidates for a given input. In this paper, our comprehensive an…
Category-Adaptive Cross-Modal Semantic Refinement and Transfer for Open-Vocabulary Multi-Label Recognition
Haijing Liu, Tao Pu, Hefeng Wu +4
Benefiting from the generalization capability of CLIP, recent vision language pre-training (VLP) models have demonstrated the ability to capture a wide range of visual concepts in…
Human-VDM: Learning Single-Image 3D Human Gaussian Splatting from Video Diffusion Models
Zhibin Liu, Haoye Dong, Aviral Chharia +1
Generating lifelike 3D humans from a single RGB image remains a challenging task in computer vision, as it requires accurate modeling of geometry, high-quality texture, and plausib…
Improving Network Interpretability via Explanation Consistency Evaluation
Hefeng Wu, Hao Jiang, Keze Wang +3
While deep neural networks have achieved remarkable performance, they tend to lack transparency in prediction. The pursuit of greater interpretability in neural networks often resu…
ID-Aligner: Enhancing Identity-Preserving Text-to-Image Generation with Reward Feedback Learning
Weifeng Chen, Jiacheng Zhang, Jie Wu +3
The rapid development of diffusion models has triggered diverse applications. Identity-preserving text-to-image generation (ID-T2I) particularly has received significant attention…
Dual-View Data Hallucination with Semantic Relation Guidance for Few-Shot Image Recognition
Hefeng Wu, Guangzhi Ye, Ziyang Zhou +3
Learning to recognize novel concepts from just a few image samples is very challenging as the learned model is easily overfitted on the few data and results in poor generalizabilit…
Contrastive Transformer Learning with Proximity Data Generation for Text-Based Person Search
Hefeng Wu, Weifeng Chen, Zhibin Liu +3
Given a descriptive text query, text-based person search (TBPS) aims to retrieve the best-matched target person from an image gallery. Such a cross-modal retrieval task is quite ch…
SQLNet: Scale-Modulated Query and Localization Network for Few-Shot Class-Agnostic Counting
Hefeng Wu, Yandong Chen, Lingbo Liu +3
The class-agnostic counting (CAC) task has recently been proposed to solve the problem of counting all objects of an arbitrary class with several exemplars given in the input image…
SketchBodyNet: A Sketch-Driven Multi-faceted Decoder Network for 3D Human Reconstruction
Fei Wang, Kongzhang Tang, Hefeng Wu +3
Reconstructing 3D human shapes from 2D images has received increasing attention recently due to its fundamental support for many high-level 3D applications. Compared with natural i…