:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Wu, Yixin, Zhang, Feiran, Shi, Tianyuan, Yin, Ruicheng, Wang, Zhenghua, Gan, Zhenliang, Wang, Xiaohua, Lv, Changze, Zheng, Xiaoqing, Huang, Xuanjing
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence Computation and Language
Online Access:	https://arxiv.org/abs/2503.06201
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

VIB-Probe: Detecting and Mitigating Hallucinations in Vision-Language Models via Variational Information Bottleneck
by: Zhang, Feiran, et al.
Published: (2026)

Searching for Best Practices in Retrieval-Augmented Generation
by: Wang, Xiaohua, et al.
Published: (2024)

Improving Continual Pre-training Through Seamless Data Packing
by: Yin, Ruicheng, et al.
Published: (2025)

Layer-Specific Scaling of Positional Encodings for Superior Long-Context Modeling
by: Wang, Zhenghua, et al.
Published: (2025)

UPLex: Fine-Grained Personality Control in Large Language Models via Unsupervised Lexical Modulation
by: Li, Tianlong, et al.
Published: (2023)

Revisiting Jailbreaking for Large Language Models: A Representation Engineering Perspective
by: Li, Tianlong, et al.
Published: (2024)

Towards Biologically Plausible Computing: A Comprehensive Comparison
by: Lv, Changze, et al.
Published: (2024)

Dendritic Localized Learning: Toward Biologically Plausible Algorithm
by: Lv, Changze, et al.
Published: (2025)

Aligning Large Language Models with Human Preferences through Representation Engineering
by: Liu, Wenhao, et al.
Published: (2023)

Advancing Spiking Neural Networks for Sequential Modeling with Central Pattern Generators
by: Lv, Changze, et al.
Published: (2024)

Efficient and Effective Time-Series Forecasting with Spiking Neural Networks
by: Lv, Changze, et al.
Published: (2024)

Enhancing the Capability and Robustness of Large Language Models through Reinforcement Learning-Driven Query Refinement
by: Wang, Xiaohua, et al.
Published: (2024)

Spiking Convolutional Neural Networks for Text Classification
by: Lv, Changze, et al.
Published: (2024)

Decoding Continuous Character-based Language from Non-invasive Brain Recordings
by: Zhang, Cenyuan, et al.
Published: (2024)

Promoting Data and Model Privacy in Federated Learning through Quantized LoRA
by: Zhu, JianHao, et al.
Published: (2024)

Biologically Plausible Learning via Bidirectional Spike-Based Distillation
by: Lv, Changze, et al.
Published: (2025)

Toward Relative Positional Encoding in Spiking Transformers
by: Lv, Changze, et al.
Published: (2025)

Beyond Single Labels: Improving Conversational Recommendation through LLM-Powered Data Augmentation
by: Xu, Haozhe, et al.
Published: (2025)

Advancing Parameter Efficiency in Fine-tuning via Representation Editing
by: Wu, Muling, et al.
Published: (2024)

SpikeCLIP: A Contrastive Language-Image Pretrained Spiking Neural Network
by: Lv, Changze, et al.
Published: (2023)

Progressive Mastery: Customized Curriculum Learning with Guided Prompting for Mathematical Reasoning
by: Wu, Muling, et al.
Published: (2025)

SATER: A Self-Aware and Token-Efficient Approach to Routing and Cascading
by: Shen, Yuanzhe, et al.
Published: (2025)

Benchmark^2: Systematic Evaluation of LLM Benchmarks
by: Qian, Qi, et al.
Published: (2026)

SpikeBERT: A Language Spikformer Learned from BERT with Knowledge Distillation
by: Lv, Changze, et al.
Published: (2023)

TripTailor: A Real-World Benchmark for Personalized Travel Planning
by: Shen, Yuanzhe, et al.
Published: (2025)

TASR: Timestep-Aware Diffusion Model for Image Super-Resolution
by: Lin, Qinwei, et al.
Published: (2024)

Timestep-Aware Diffusion Model for Extreme Image Rescaling
by: Wang, Ce, et al.
Published: (2024)

AsyncDiff: Asynchronous Timestep Conditioning for Enhanced Text-to-Image Diffusion Inference
by: Xu, Longhuan, et al.
Published: (2025)

Learning Query-Specific Rubrics from Human Preferences for DeepResearch Report Generation
by: Lv, Changze, et al.
Published: (2026)

Timestep-Compressed Attack on Spiking Neural Networks through Timestep-Level Backpropagation
by: Kang, Donghwa, et al.
Published: (2025)

Diffusion Models are Geometry Critics: Single Image 3D Editing Using Pre-Trained Diffusion Priors
by: Wang, Ruicheng, et al.
Published: (2024)

Timestep-Aware Correction for Quantized Diffusion Models
by: Yao, Yuzhe, et al.
Published: (2024)

Exploring Multi-Timestep Multi-Stage Diffusion Features for Hyperspectral Image Classification
by: Zhou, Jingyi, et al.
Published: (2023)

Populating cellular metamaterials on the extrema of attainable elasticity through neuroevolution
by: Yan, Maohua, et al.
Published: (2024)

Parallel Training in Spiking Neural Networks
by: Huang, Yanbin, et al.
Published: (2026)

Compute Only 16 Tokens in One Timestep: Accelerating Diffusion Transformers with Cluster-Driven Feature Caching
by: Zheng, Zhixin, et al.
Published: (2025)

ECC-SNN: Cost-Effective Edge-Cloud Collaboration for Spiking Neural Networks
by: Yu, Di, et al.
Published: (2025)

Model Utility Law: Evaluating LLMs beyond Performance through Mechanism Interpretable Metric
by: Cao, Yixin, et al.
Published: (2025)

Generative Multimodal Pretraining with Discrete Diffusion Timestep Tokens
by: Pan, Kaihang, et al.
Published: (2025)

ERTACache: Error Rectification and Timesteps Adjustment for Efficient Diffusion
by: Peng, Xurui, et al.
Published: (2025)