2 citations · 2 across the 15 of their papers we have counts for
18 papers
From Short Clips to Real-Time Streams: Identity-Aware Supervision and Context-Efficient Generation for Video Face Swapping
Zekai Luo, Yuwei Liang, Ruiqi Ma +8
Video face swapping transfers the reference identity to a target video while preserving its other attributes and motion. Despite recent progress in reference-guided flow-based meth…
SACQ: Structured Decoding with Memory-Conditioned Refinement for Long-Horizon Forecasting
Guo Cheng, Zhengzhuo Xu, Chenchen Jing +1
Long-term time series forecasting (LTSF) models predominantly employ patch-based encoders terminated by a flatten readout head that maps the entire encoded historical memory to all…
Metric-Bench: Exploring In-context Spatial Metric Reasoning in VLMs for Indoor Scenes
Yuling Xi, Haokai Zhang, Muzhi Zhu +10
Metric reasoning is a critical and challenging task for Vision Language Models (VLMs), playing a pivotal role in embodied AI tasks such as robotic manipulation and autonomous navig…
ForeDreamer: A Self-Evolving Dual-Agent Memory Architecture for Future Event Prediction
Linhao Zhong, Zongze Du, Linyu Wu +6
Open-web future event prediction requires agents to distill reliable signals from noisy, redundant, and incomplete evidence. Existing retrieval/memory mechanisms directly feed retr…
Efficient Self-Evaluation for Diffusion Language Models via Sequence Regeneration
Linhao Zhong, Linyu Wu, Wen Wang +5
Diffusion large language models (dLLMs) have recently attracted significant attention for their ability to enhance diversity, controllability, and parallelism. However, their non-s…
Differentiate-and-Inject: Enhancing VLAs via Functional Differentiation Induced by In-Parameter Structural Reasoning
Jingyi Hou, Leyu Zhou, Chenchen Jing +3
As robots are expected to perform increasingly diverse tasks, they must understand not only low-level actions but also the higher-level structure that determines how a task should…
Beyond Hard Masks: Progressive Token Evolution for Diffusion Language Models
Linhao Zhong, Linyu Wu, Bozhen Fang +6
Diffusion Language Models (DLMs) offer a promising alternative for language modeling by enabling parallel decoding through iterative refinement. However, most DLMs rely on hard bin…
Preserving Source Video Realism: High-Fidelity Face Swapping for Cinematic Quality
Zekai Luo, Zongze Du, Zhouhang Zhu +7
Video face swapping is crucial in film and entertainment production, where achieving high fidelity and temporal consistency over long and complex video sequences remains a signific…
Unified Open-World Segmentation with Multi-Modal Prompts
Yang Liu, Yufei Yin, Chenchen Jing +7
In this work, we present COSINE, a unified open-world segmentation model that consolidates open-vocabulary segmentation and in-context segmentation with multi-modal prompts (e.g.,…
Evolutionary Profiles for Protein Fitness Prediction
Jigang Fan, Xiaoran Jiao, Shengdong Lin +5
Predicting the fitness impact of mutations is central to protein engineering but constrained by limited assays relative to the size of sequence space. Protein language models (pLMs…
Learning by Imagining: Debiased Feature Augmentation for Compositional Zero-Shot Learning
Haozhe Zhang, Chenchen Jing, Mingyu Liu +2
Compositional Zero-Shot Learning (CZSL) aims to recognize unseen attribute-object compositions by learning prior knowledge of seen primitives, \textit{i.e.}, attributes and objects…
MM-BrowseComp: A Comprehensive Benchmark for Multimodal Browsing Agents
Shilong Li, Xingyuan Bu, Wenjie Wang +22
AI agents with advanced reasoning and tool-use capabilities have demonstrated impressive performance in web browsing for deep search. However, existing benchmarks such as BrowseCom…
Time Is a Feature: Exploiting Temporal Dynamics in Diffusion Language Models
Wen Wang, Bozhen Fang, Chenchen Jing +6
Diffusion large language models (dLLMs) generate text through iterative denoising, yet current decoding strategies discard rich intermediate predictions in favor of the final outpu…
PerturboLLaVA: Reducing Multimodal Hallucinations with Perturbative Visual Training
Cong Chen, Mingyu Liu, Chenchen Jing +5
This paper aims to address the challenge of hallucinations in Multimodal Large Language Models (MLLMs) particularly for dense image captioning tasks. To tackle the challenge, we id…
Learning Visual Proxy for Compositional Zero-Shot Learning
Shiyu Zhang, Cheng Yan, Yang Liu +3
Compositional Zero-Shot Learning (CZSL) aims to recognize novel attribute-object compositions by leveraging knowledge from seen compositions. Current methods align textual prototyp…
Unleashing the Potential of the Diffusion Model in Few-shot Semantic Segmentation
Muzhi Zhu, Yang Liu, Zekai Luo +5
The Diffusion Model has not only garnered noteworthy achievements in the realm of image generation but has also demonstrated its potential as an effective pretraining method utiliz…
A Simple Image Segmentation Framework via In-Context Examples
Yang Liu, Chenchen Jing, Hengtao Li +4
Recently, there have been explorations of generalist segmentation models that can effectively tackle a variety of image segmentation tasks within a unified in-context learning fram…
CoLeCLIP: Open-Domain Continual Learning via Joint Task Prompt and Vocabulary Learning
Yukun Li, Guansong Pang, Wei Suo +6
This paper explores the problem of continual learning (CL) of vision-language models (VLMs) in open domains, where the models need to perform continual updating and inference on a…