:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Tong, Jintao, Jin, Wenwei, Qin, Pengda, Li, Anqi, Zou, Yixiong, Li, Yuhong, Li, Yuhua, Li, Ruixuan
Formato:	Preprint
Publicado:	2025
Materias:	Computer Vision and Pattern Recognition Artificial Intelligence Computation and Language
Acceso en línea:	https://arxiv.org/abs/2505.19536
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Towards Trustworthy Multimodal Moderation via Policy-Aligned Reasoning and Hierarchical Labeling
por: Li, Anqi, et al.
Publicado: (2025)

Lightweight Frequency Masker for Cross-Domain Few-Shot Semantic Segmentation
por: Tong, Jintao, et al.
Publicado: (2024)

Self-Disentanglement and Re-Composition for Cross-Domain Few-Shot Segmentation
por: Tong, Jintao, et al.
Publicado: (2025)

Delve into Base-Novel Confusion: Redundancy Exploration for Few-Shot Class-Incremental Learning
por: Zhou, Haichen, et al.
Publicado: (2024)

Adapter Naturally Serves as Decoupler for Cross-Domain Few-Shot Semantic Segmentation
por: Tong, Jintao, et al.
Publicado: (2025)

MICM: Rethinking Unsupervised Pretraining for Enhanced Few-shot Learning
por: Zhang, Zhenyu, et al.
Publicado: (2024)

Addressing Exacerbated Attention Sink for Source-Free Cross-Domain Few-Shot Learning
por: Yi, Shuai, et al.
Publicado: (2026)

Revisiting Continuity of Image Tokens for Cross-domain Few-shot Learning
por: Yi, Shuai, et al.
Publicado: (2025)

Revisiting Pool-based Prompt Learning for Few-shot Class-incremental Learning
por: Jiang, Yongwei, et al.
Publicado: (2025)

Reconstruction Target Matters in Masked Image Modeling for Cross-Domain Few-Shot Learning
por: Ma, Ran, et al.
Publicado: (2024)

Random Registers for Cross-Domain Few-Shot Learning
por: Yi, Shuai, et al.
Publicado: (2025)

Remedying Target-Domain Astigmatism for Cross-Domain Few-Shot Object Detection
por: Jiang, Yongwei, et al.
Publicado: (2026)

Improving CLIP Adaptation by Breaking Tail Alignment for Source-Free Cross-Domain Few-Shot Learning
por: Yi, Shuai, et al.
Publicado: (2026)

The Devil is in Low-Level Features for Cross-Domain Few-Shot Segmentation
por: Liu, Yuhan, et al.
Publicado: (2025)

Interpretable Cross-Domain Few-Shot Learning with Rectified Target-Domain Local Alignment
por: Zhao, Yaze, et al.
Publicado: (2026)

FlowCut: Unsupervised Video Instance Segmentation via Temporal Mask Matching
por: Sari, Alp Eren, et al.
Publicado: (2025)

Learning Unknowns from Unknowns: Diversified Negative Prototypes Generator for Few-Shot Open-Set Recognition
por: Zhang, Zhenyu, et al.
Publicado: (2024)

Mind the Discriminability Trap in Source-Free Cross-domain Few-shot Learning
por: Zhang, Zhenyu, et al.
Publicado: (2026)

Flatten Long-Range Loss Landscapes for Cross-Domain Few-Shot Learning
por: Zou, Yixiong, et al.
Publicado: (2024)

Compositional Few-Shot Class-Incremental Learning
por: Zou, Yixiong, et al.
Publicado: (2024)

Reviving In-domain Fine-tuning Methods for Source-Free Cross-domain Few-shot Learning
por: Zhao, Yaze, et al.
Publicado: (2026)

ExPO-HM: Learning to Explain-then-Detect for Hateful Meme Detection
por: Mei, Jingbiao, et al.
Publicado: (2025)

Mitigating Hallucinations in Large Vision-Language Models by Adaptively Constraining Information Flow
por: Bai, Jiaqi, et al.
Publicado: (2025)

Less Redundancy: Boosting Practicality of Vision Language Model in Walking Assistants
por: Li, Chongyang, et al.
Publicado: (2025)

Beyond Higher Rank: Token-wise Input-Output Projections for Efficient Low-Rank Adaptation
por: Li, Shiwei, et al.
Publicado: (2025)

Adversarial Attack for Explanation Robustness of Rationalization Models
por: Zhang, Yuankai, et al.
Publicado: (2024)

From Redundancy to Relevance: Information Flow in LVLMs Across Reasoning Tasks
por: Zhang, Xiaofeng, et al.
Publicado: (2024)

Tokens for Learning, Tokens for Unlearning: Mitigating Membership Inference Attacks in Large Language Models via Dual-Purpose Training
por: Tran, Toan, et al.
Publicado: (2025)

MuDPT: Multi-modal Deep-symphysis Prompt Tuning for Large Pre-trained Vision-Language Models
por: Miao, Yongzhu, et al.
Publicado: (2023)

FlowMM: Cross-Modal Information Flow Guided KV Cache Merging for Efficient Multimodal Context Inference
por: Li, Kunxi, et al.
Publicado: (2025)

Sketch-in-Latents: Eliciting Unified Reasoning in MLLMs
por: Tong, Jintao, et al.
Publicado: (2025)

SwimBird: Eliciting Switchable Reasoning Mode in Hybrid Autoregressive MLLMs
por: Tong, Jintao, et al.
Publicado: (2026)

FlowBench: Revisiting and Benchmarking Workflow-Guided Planning for LLM-based Agents
por: Xiao, Ruixuan, et al.
Publicado: (2024)

ThinkLess: A Training-Free Inference-Efficient Method for Reducing Reasoning Redundancy
por: Li, Gengyang, et al.
Publicado: (2025)

UniNote: A Unified Embedding Model for Multimodal Representation and Ranking
por: Zhao, Jinghan, et al.
Publicado: (2026)

Beyond Steering Vector: Flow-based Activation Steering for Inference-Time Intervention
por: Jin, Zehao, et al.
Publicado: (2026)

Large Language Model (LLM) AI text generation detection based on transformer deep learning algorithm
por: Mo, Yuhong, et al.
Publicado: (2024)

Migician: Revealing the Magic of Free-Form Multi-Image Grounding in Multimodal Large Language Models
por: Li, You, et al.
Publicado: (2025)

Rethinking the Roles of Large Language Models in Chinese Grammatical Error Correction
por: Li, Yinghui, et al.
Publicado: (2024)

Rethinking Bottlenecks in Safety Fine-Tuning of Vision Language Models
por: Ding, Yi, et al.
Publicado: (2025)