285 citations · 736 across the 85 of their papers we have counts for
29 papers · 1 filter
OFL-SAM2: Prompt SAM2 with Online Few-shot Learner for Efficient Medical Image Segmentation
Meng Lan, Lefei Zhang, Xiaomeng Li
The Segment Anything Model 2 (SAM2) has demonstrated remarkable promptable visual segmentation capabilities in video data, showing potential for extension to medical image segmenta…
TGC-Net: A Structure-Aware and Semantically-Aligned Framework for Text-Guided Medical Image Segmentation
Gaoren Lin, Huangxuan Zhao, Yuan Xiong +3
Text-guided medical segmentation enhances segmentation accuracy by utilizing clinical reports as auxiliary information. However, existing methods typically rely on unaligned image…
EvoIR: Towards All-in-One Image Restoration via Evolutionary Frequency Modulation
Jiaqi Ma, Shengkai Hu, Xu Zhang +4
All-in-One Image Restoration (AiOIR) tasks often involve diverse degradation that require robust and versatile strategies. However, most existing approaches typically lack explicit…
DiffusionDriveV2: Reinforcement Learning-Constrained Truncated Diffusion Modeling in End-to-End Autonomous Driving
Jialv Zou, Shaoyu Chen, Bencheng Liao +6
Generative diffusion models for end-to-end autonomous driving often suffer from mode collapse, tending to generate conservative and homogeneous behaviors. While DiffusionDrive empl…
ClusIR: Towards Cluster-Guided All-in-One Image Restoration
Shengkai Hu, Jiaqi Ma, Xu Zhang +3
All-in-One Image Restoration (AiOIR) aims to recover high-quality images from diverse degradations within a unified framework. However, existing methods often fail to explicitly mo…
Neural Discrete Representation Learning for Sparse-View CBCT Reconstruction: From Algorithm Design to Prospective Multicenter Clinical Evaluation
Haoshen Wang, Lei Chen, Wei-Hua Zhang +13
Cone beam computed tomography (CBCT)-guided puncture has become an established approach for diagnosing and treating early- to mid-stage thoracic tumours, yet the associated radiati…
Scaling LLM Speculative Decoding: Non-Autoregressive Forecasting in Large-Batch Scenarios
Luohe Shi, Zuchao Li, Lefei Zhang +3
Speculative decoding accelerates LLM inference by utilizing otherwise idle computational resources during memory-to-chip data transfer. Current speculative decoding methods typical…
ResAD: Normalized Residual Trajectory Modeling for End-to-End Autonomous Driving
Zhiyu Zheng, Shaoyu Chen, Haoran Yin +5
End-to-end autonomous driving (E2EAD) systems, which learn to predict future trajectories directly from sensor data, are fundamentally challenged by the inherent spatio-temporal im…
ToM: Leveraging Tree-oriented MapReduce for Long-Context Reasoning in Large Language Models
Jiani Guo, Zuchao Li, Jie Wu +5
Large Language Models (LLMs), constrained by limited context windows, often face significant performance degradation when reasoning over long contexts. To address this, Retrieval-A…
Proto-Former: Unified Facial Landmark Detection by Prototype Transformer
Shengkai Hu, Haozhe Qi, Jun Wan +4
Recent advances in deep learning have significantly improved facial landmark detection. However, existing facial landmark detection datasets often define different numbers of landm…
Information-Theoretic Reward Modeling for Stable RLHF: Detecting and Mitigating Reward Hacking
Yuchun Miao, Liang Ding, Sen Zhang +3
Despite the success of Reinforcement Learning from Human Feedback (RLHF) in aligning language models with human values, reward hacking-or reward over-optimization-remains a major c…
A Multi-Language Object-Oriented Programming Benchmark for Large Language Models
Shuai Wang, Liang Ding, Li Shen +4
Establishing fair and robust benchmarks is essential for evaluating intelligent code generation by large language models (LLMs). Our survey of 35 existing benchmarks uncovers three…
OmniBridge: Unified Multimodal Understanding, Generation, and Retrieval via Latent Space Alignment
Teng Xiao, Zuchao Li, Lefei Zhang
Recent advances in multimodal large language models (LLMs) have led to significant progress in understanding, generation, and retrieval tasks. However, current solutions often trea…
CoViPAL: Layer-wise Contextualized Visual Token Pruning for Large Vision-Language Models
Zicong Tang, Ziyang Ma, Suqing Wang +5
Large Vision-Language Models (LVLMs) process multimodal inputs consisting of text tokens and vision tokens extracted from images or videos. Due to the rich visual information, a si…
S5: Scalable Semi-Supervised Semantic Segmentation in Remote Sensing
Liang Lv, Di Wang, Jing Zhang +1
Semi-supervised semantic segmentation (S4) has advanced remote sensing (RS) analysis by leveraging unlabeled data through pseudo-labeling and consistency learning. However, existin…
KV-Latent: Dimensional-level KV Cache Reduction with Frequency-aware Rotary Positional Embedding
Luohe Shi, Zuchao Li, Lefei Zhang +3
Large language models (LLMs) based on Transformer Decoders have become the preferred choice for conversational generative AI. Despite the overall superiority of the Decoder archite…
SpindleKV: A Novel KV Cache Reduction Method Balancing Both Shallow and Deep Layers
Zicong Tang, Shi Luohe, Zuchao Li +4
Large Language Models (LLMs) have achieved impressive accomplishments in recent years. However, the increasing memory consumption of KV cache has possessed a significant challenge…
Segment First or Comprehend First? Explore the Limit of Unsupervised Word Segmentation with Large Language Models
Zihong Zhang, Liqi He, Zuchao Li +3
Word segmentation stands as a cornerstone of Natural Language Processing (NLP). Based on the concept of "comprehend first, segment later", we propose a new framework to explore the…
Refining Few-Step Text-to-Multiview Diffusion via Reinforcement Learning
Ziyi Zhang, Li Shen, Deheng Ye +5
Text-to-multiview (T2MV) diffusion models have shown great promise in generating multiple views of a scene from a single text prompt. While few-step backbones enable real-time T2MV…
MambaMoE: Mixture-of-Spectral-Spatial-Experts State Space Model for Hyperspectral Image Classification
Yichu Xu, Di Wang, Hongzan Jiao +2
Mamba-based models have recently demonstrated significant potential in hyperspectral image (HSI) classification, primarily due to their ability to perform contextual modeling with…
Model Hemorrhage and the Robustness Limits of Large Language Models
Ziyang Ma, Zuchao Li, Lefei Zhang +4
Large language models (LLMs) demonstrate strong performance across natural language processing tasks, yet undergo significant performance degradation when modified for deployment t…
RS2-SAM2: Customized SAM2 for Referring Remote Sensing Image Segmentation
Fu Rong, Meng Lan, Qian Zhang +1
Referring Remote Sensing Image Segmentation (RRSIS) aims to segment target objects in remote sensing (RS) images based on textual descriptions. Although Segment Anything Model 2 (S…
Label Drop for Multi-Aspect Relation Modeling in Universal Information Extraction
Lu Yang, Jiajia Li, En Ci +3
Universal Information Extraction (UIE) has garnered significant attention due to its ability to address model explosion problems effectively. Extractive UIE can achieve strong perf…
NOTA: Multimodal Music Notation Understanding for Visual Large Language Model
Mingni Tang, Jiajia Li, Lu Yang +5
Symbolic music is represented in two distinct forms: two-dimensional, visually intuitive score images, and one-dimensional, standardized text annotation sequences. While large lang…