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Optimizing KBQA by Correcting LLM-Generated Non-Executable Logical Form Through Knowledge-Assisted Path Reconstruction

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Parameterization of Volume Sampling for Active Learning of Radiance Field

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Bridging the Language Gap: Uncovering and Aligning Shared Circuits for Multi-Hop Reasoning in Multilingual LLMs

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Semantic Voting: A Self-Evaluation-Free Approach for Efficient LLM Self-Improvement on Unverifiable Open-ended Tasks

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Characterizing Submanifold Region for Out-of-Distribution Detection

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Consistent prompt learning for vision-language models

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Federated Principal Component Analysis for Vertically Partitioned Data

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InsGNN: Interpretable spatio-temporal graph neural networks via information bottleneck

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MetaGeno: a chromosome-wise multi-task genomic framework for ischaemic stroke risk prediction

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Out-of-Distribution Detection with Virtual Outlier Smoothing

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SENA: Leveraging set-level consistency adversarial learning for robust pre-trained language model adaptation

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Supplementary Prompt Learning for Vision-Language Models

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Component-Level Segmentation for Oracle Bone Inscription Decipherment

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Detecting Generated Images by Fitting Natural Image Distributions

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Distributional Prototype Learning for Out-of-distribution Detection

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Enhancing Target-unspecific Tasks through a Features Matrix

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Epistemic Uncertainty for Generated Image Detection

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FedGPS: Statistical Rectification Against Data Heterogeneity in Federated Learning

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Hot-pluggable Federated Learning: Bridging General and Personalized FL via Dynamic Selection

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Interpret and Improve In-Context Learning via the Lens of Input-Label Mappings

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Leveraging Submodule Linearity Enhances Task Arithmetic Performance in LLMs

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Mitigating Forgetting in Adapting Pre-trained Language Models to Text Processing Tasks via Consistency Alignment

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MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detection

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Towards Generalizable Detector for Generated Image

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Tracing and Dissecting How LLMs Recall Factual Knowledge for Real World Questions

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Unlocker: Disentangle the Deadlock of Learning between Label-noisy and Long-tailed Data

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Expert-level diagnosis of pediatric posterior fossa tumors via consistency calibration

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Component-Level Oracle Bone Inscription Retrieval

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ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection

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Enhancing Multiple Dimensions of Trustworthiness in LLMs via Sparse Activation Control

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Enhancing One-Shot Federated Learning Through Data and Ensemble Co-Boosting

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Federated Learning with Extremely Noisy Clients via Negative Distillation

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From Yes-Men to Truth-Tellers: Addressing Sycophancy in Large Language Models with Pinpoint Tuning

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Interpreting and Improving Large Language Models in Arithmetic Calculation

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Learning to Shape In-distribution Feature Space for Out-of-distribution Detection

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NoiseDiffusion: Correcting Noise for Image Interpolation with Diffusion Models beyond Spherical Linear Interpolation

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Out-of-Distribution Detection with Negative Prompts

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Robust Training of Federated Models with Extremely Label Deficiency

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Continual Named Entity Recognition without Catastrophic Forgetting

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FedFed: Feature Distillation against Data Heterogeneity in Federated Learning

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Hard Sample Matters a Lot in Zero-Shot Quantization

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Invariant Learning via Probability of Sufficient and Necessary Causes

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Learning to Augment Distributions for Out-of-Distribution Detection

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Moderately Distributional Exploration for Domain Generalization

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Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization

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SODA: Robust Training of Test-Time Data Adaptors

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CausalAdv: Adversarial Robustness Through the Lens of Causality

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Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs

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Meta Convolutional Neural Networks for Single Domain Generalization

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Prompt Distribution Learning

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Towards Lightweight Black-Box Attacks Against Deep Neural Networks

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Understanding and Improving Graph Injection Attack by Promoting Unnoticeability

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Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning

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Watermarking for Out-of-distribution Detection

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Class-Disentanglement and Applications in Adversarial Detection and Defense

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Principal Component Adversarial Example

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Dual-Path Distillation: A Unified Framework to Improve Black-Box Attacks

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