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世界中で発行される人工知能関連の論文をまとめるページです。
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WhaleVAD-BPN: Improving Baleen Whale Call Detection with Boundary Proposal Networks and Post-processing Optimisation

The Gray Zone of Faithfulness: Taming Ambiguity in Unfaithfulness Detection

Towards General Modality Translation with Contrastive and Predictive Latent Diffusion Bridge

BUSTED at AraGenEval Shared Task: A Comparative Study of Transformer-Based Models for Arabic AI-Generated Text Detection

Steering Evaluation-Aware Language Models to Act Like They Are Deployed

DB-FGA-Net: Dual Backbone Frequency Gated Attention Network for Multi-Class Brain Tumor Classification with Grad-CAM Interpretability

日常的な検査データを用いた早期癌検出の実現可能性の評価：不均衡なデータセットにおける機械学習アプローチの評価

On the Structure of Stationary Solutions to McKean-Vlasov Equations with Applications to Noisy Transformers

ShapeX: Shapelet-Driven Post Hoc Explanations for Time Series Classification Models

Using Non-Expert Data to Robustify Imitation Learning via Offline Reinforcement Learning

Imbalanced Gradients in RL Post-Training of Multi-Task LLMs

What Makes a Good Curriculum? Disentangling the Effects of Data Ordering on LLM Mathematical Reasoning

Noise-corrected GRPO: From Noisy Rewards to Unbiased Gradients

UNO-Bench: A Unified Benchmark for Exploring the Compositional Law Between Uni-modal and Omni-modal in OmniModels

ADPO: Anchored Direct Preference Optimization

Every Step Evolves: Scaling Reinforcement Learning for Trillion-Scale Thinking Model

MIN-Merging: Merge the Important Neurons for Model Merging

When Intelligence Fails: An Empirical Study on Why LLMs Struggle with Password Cracking

From Flows to Words: Can Zero-/Few-Shot LLMs Detect Network Intrusions? A Grammar-Constrained, Calibrated Evaluation on UNSW-NB15

SimBench: Benchmarking the Ability of Large Language Models to Simulate Human Behaviors

GOOD: Training-Free Guided Diffusion Sampling for Out-of-Distribution Detection

UNDREAM: Bridging Differentiable Rendering and Photorealistic Simulation for End-to-end Adversarial Attacks

The Chameleon Nature of LLMs: Quantifying Multi-Turn Stance Instability in Search-Enabled Language Models

ESCA: Contextualizing Embodied Agents via Scene-Graph Generation

Incomplete Multi-view Clustering via Hierarchical Semantic Alignment and Cooperative Completion

Deflanderization for Game Dialogue: Balancing Character Authenticity with Task Execution in LLM-based NPCs

Evidence Without Injustice: A New Counterfactual Test for Fair Algorithms

Beyond Seeing: Evaluating Multimodal LLMs on Tool-Enabled Image Perception, Transformation, and Reasoning

Automatic Music Sample Identification with Multi-Track Contrastive Learning

DiffHeads: Differential Analysis and Inference-Time Masking of Bias Heads in Large Language Models

Training-Free In-Context Forensic Chain for Image Manipulation Detection and Localization

Uncovering Singularities in Feynman Integrals via Machine Learning

Beyond Fertility: Analyzing STRR as a Metric for Multilingual Tokenization Evaluation

Token Is All You Price

LLM4Cell: A Survey of Large Language and Agentic Models for Single-Cell Biology

IKNet: Interpretable Stock Price Prediction via Keyword-Guided Integration of News and Technical Indicators

Smartphone-based iris recognition through high-quality visible-spectrum iris image capture.V2

Tiny but Mighty: A Software-Hardware Co-Design Approach for Efficient Multimodal Inference on Battery-Powered Small Devices

Feasibility-Aware Decision-Focused Learning for Predicting Parameters in the Constraints

Unmasking Puppeteers: Leveraging Biometric Leakage to Disarm Impersonation in AI-based Videoconferencing

SpineBench: A Clinically Salient, Level-Aware Benchmark Powered by the SpineMed-450k Corpus

Holistic Order Prediction in Natural Scenes

Editable Noise Map Inversion: Encoding Target-image into Noise For High-Fidelity Image Manipulation

LUQ: Layerwise Ultra-Low Bit Quantization for Multimodal Large Language Models

Aligning LLMs for Multilingual Consistency in Enterprise Applications

Open-Vocabulary Spatio-Temporal Scene Graph for Robot Perception and Teleoperation Planning

Automatic Discovery of One Parameter Subgroups of $SO(n)$

Can Less Precise Be More Reliable? A Systematic Evaluation of Quantization's Impact on CLIP Beyond Accuracy

WolBanking77: Wolof Banking Speech Intent Classification Dataset

UniPixel: Unified Object Referring and Segmentation for Pixel-Level Visual Reasoning

Unveiling m-Sharpness Through the Structure of Stochastic Gradient Noise

EvoBrain: Dynamic Multi-Channel EEG Graph Modeling for Time-Evolving Brain Networks

BTL-UI: Blink-Think-Link Reasoning Model for GUI Agent

TreeIRL: Safe Urban Driving with Tree Search and Inverse Reinforcement Learning

Your Compiler is Backdooring Your Model: Understanding and Exploiting Compilation Inconsistency Vulnerabilities in Deep Learning Compilers

Membership Inference Attacks on Recommender System: A Survey

Reconstruction Alignment Improves Unified Multimodal Models

Deriving Transformer Architectures as Implicit Multinomial Regression

The Complexity Trap: Simple Observation Masking Is as Efficient as LLM Summarization for Agent Context Management

ClaimGen-CN: A Large-scale Chinese Dataset for Legal Claim Generation

The Role of AI in Facilitating Interdisciplinary Collaboration: Evidence from AlphaFold

Score-informed Neural Operator for Enhancing Ordering-based Causal Discovery

TaoSR1: The Thinking Model for E-commerce Relevance Search

A Data-driven ML Approach for Maximizing Performance in LLM-Adapter Serving

Beyond Ten Turns: Unlocking Long-Horizon Agentic Search with Large-Scale Asynchronous RL

CannyEdit: Selective Canny Control and Dual-Prompt Guidance for Training-Free Image Editing

The ISLab Solution to the Algonauts Challenge 2025: A Multimodal Deep Learning Approach to Brain Response Prediction

EmoSteer-TTS: Fine-Grained and Training-Free Emotion-Controllable Text-to-Speech via Activation Steering

PESTO: Real-Time Pitch Estimation with Self-supervised Transposition-equivariant Objective

BikeBench: A Bicycle Design Benchmark for Generative Models with Objectives and Constraints

Trusted Knowledge Extraction for Operations and Maintenance Intelligence

CapRecover: A Cross-Modality Feature Inversion Attack Framework on Vision Language Models

ReXGroundingCT: A 3D Chest CT Dataset for Segmentation of Findings from Free-Text Reports

DmC: Nearest Neighbor Guidance Diffusion Model for Offline Cross-domain Reinforcement Learning

Detect Any Sound: Open-Vocabulary Sound Event Detection with Multi-Modal Queries

PhysGym: Benchmarking LLMs in Interactive Physics Discovery with Controlled Priors

A Lightweight Gradient-based Causal Discovery Framework with Applications to Complex Industrial Processes

Ground-Compose-Reinforce: Grounding Language in Agentic Behaviours using Limited Data

Through the River: Understanding the Benefit of Schedule-Free Methods for Language Model Training

Context-Aware Regularization with Markovian Integration for Attention-Based Nucleotide Analysis

Vision Foundation Models as Effective Visual Tokenizers for Autoregressive Image Generation

The Cross-Lingual Cost: Retrieval Biases in RAG over Arabic-English Corpora

Unifying Re-Identification, Attribute Inference, and Data Reconstruction Risks in Differential Privacy

Agent KB: Leveraging Cross-Domain Experience for Agentic Problem Solving

OpenS2S: Advancing Fully Open-Source End-to-End Empathetic Large Speech Language Model

Rethinking and Exploring String-Based Malware Family Classification in the Era of LLMs and RAG

Deep Learning Atmospheric Models Reliably Simulate Out-of-Sample Land Heat and Cold Wave Frequencies

ARF-RLHF: Adaptive Reward-Following for RLHF through Emotion-Driven Self-Supervision and Trace-Biased Dynamic Optimization

Echo State Transformer: Attention Over Finite Memories

Reasoning as an Adaptive Defense for Safety

Curious Causality-Seeking Agents Learn Meta Causal World

DeepOmni: Towards Seamless and Smart Speech Interaction with Adaptive Modality-Specific MoE

FlightKooba: A Fast Interpretable FTP Model

Thought Anchors: Which LLM Reasoning Steps Matter?

MEXA: Towards General Multimodal Reasoning with Dynamic Multi-Expert Aggregation

Identifiability of Deep Polynomial Neural Networks

Cohort Discovery: A Survey on LLM-Assisted Clinical Trial Recruitment

Distributional Training Data Attribution: What do Influence Functions Sample?

KungfuBot: Physics-Based Humanoid Whole-Body Control for Learning Highly-Dynamic Skills

Unsupervised Document and Template Clustering using Multimodal Embeddings

GOOD: Training-Free Guided Diffusion Sampling for Out-of-Distribution Detection

Created by

Haebom

作者

Xin Gao, Jiyao Liu, Guanghao Li, Yueming Lyu, Jianxiong Gao, Weichen Yu, Ningsheng Xu, Liang Wang, Caifeng Shan, Ziwei Liu, Chenyang Si

概要

この論文では、テキスト画像拡散モデルを使用してOOD（Out-of-Distribution）サンプルを合成する新しいフレームワークであるGOOD（Guided OOD Generation）を提案します。従来の方法のLimitationsである意味的不安定性と不適切な移動多様性を解決するために、GOODは既知の識別分類分類器を使用して拡散サンプリング軌跡を直接ODD領域に導きます。 Image-levelとfeature-levelのデュアルガイドにより、より制御可能で多様なOODサンプル生成を可能にします。さらに、画像と特徴の不一致を適応的に組み合わせる統合されたOODスコアを導入することで、検出ロバスト性を向上させます。 GOODで生成されたサンプルでトレーニングすることで、OOD検出性能を大幅に向上させることができます。

Takeaways、Limitations

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Takeaways：

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OODサンプル生成のための新しいフレームワーク提案（GOOD）。

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Image-level と feature-level デュアルガイドによる OOD サンプリング制御と多様性の向上

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統合OODスコアによるOOD検出ロバスト性の向上

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GOODで生成されたサンプルを活用したOOD検出性能改善実証。

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Limitations：

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既存のID分類器に依存しています。

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具体的なLimitationsは論文に詳細に記載されていない。 (論文の要約のみに基づいて作成)

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