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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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Watermarking and Anomaly Detection in Machine Learning Models for LORA RF Fingerprinting

Vulnerable Agent Identification in Large-Scale Multi-Agent Reinforcement Learning

Sea-ing Through Scattered Rays: Revisiting the Image Formation Model for Realistic Underwater Image Generation

DPANet: Dual Pyramid Attention Network for Multivariate Time Series Forecasting

MeanFlowSE: one-step generative speech enhancement via conditional mean flow

Empathy-R1: A Chain-of-Empathy and Reinforcement Learning Framework for Long-Form Mental Health Support

Threat Modeling for Enhancing Security of IoT Audio Classification Devices under a Secure Protocols Framework

AToken: A Unified Tokenizer for Vision

TGPO: Tree-Guided Preference Optimization for Robust Web Agent Reinforcement Learning

Comprehensive Evaluation of CNN-Based Audio Tagging Models on Resource-Constrained Devices

MapAnything: Universal Feed-Forward Metric 3D Reconstruction

Improving Anomalous Sound Detection with Attribute-aware Representation from Domain-adaptive Pre-training

Hardness, Structural Knowledge, and Opportunity: An Analytical Framework for Modular Performance Modeling

Benchmark of stylistic variation in LLM-generated texts

SWE-Effi: Re-Evaluating Software AI Agent System Effectiveness Under Resource Constraints

Structure Matters: Brain Graph Augmentation via Learnable Edge Masking for Data-efficient Psychiatric Diagnosis

DischargeSim: A Simulation Benchmark for Educational Doctor-Patient Communication at Discharge

Riemannian Batch Normalization: A Gyro Approach

On the Security of Tool-Invocation Prompts for LLM-Based Agentic Systems: An Empirical Risk Assessment

MIDOG 2025: Mitotic Figure Detection with Attention-Guided False Positive Correction

Do Retrieval Augmented Language Models Know When They Don't Know?

LongCat-Flash Technical Report

MedCOD: Enhancing English-to-Spanish Medical Translation of Large Language Models Using Enriched Chain-of-Dictionary Framework

Middo: Model-Informed Dynamic Data Optimization for Enhanced LLM Fine-Tuning via Closed-Loop Learning

PVPO: Pre-Estimated Value-Based Policy Optimization for Agentic Reasoning

CORE-RAG: Lossless Compression for Retrieval-Augmented LLMs via Reinforcement Learning

OpenWHO: A Document-Level Parallel Corpus for Health Translation in Low-Resource Languages

Subjective Behaviors and Preferences in LLM: Language of Browsing

Using Natural Language for Human-Robot Collaboration in the Real World

RegionMed-CLIP: A Region-Aware Multimodal Contrastive Learning Pre-trained Model for Medical Image Understanding

Causal2Vec: Improving Decoder-only LLMs as Versatile Embedding Models

VLA-Mark: A cross modal watermark for large vision-language alignment model

Deformable Dynamic Convolution for Accurate yet Efficient Spatio-Temporal Traffic Prediction

Deep Reinforcement Learning with Gradient Eligibility Traces

Generating Moving 3D Soundscapes with Latent Diffusion Models

Capturing Polysemanticity with PRISM: A Multi-Concept Feature Description Framework

Discrete Diffusion in Large Language and Multimodal Models: A Survey

DualEdit: Dual Editing for Knowledge Updating in Vision-Language Models

Algorithmic Fairness: Not a Purely Technical but Socio-Technical Property

OptiScene: LLM-driven Indoor Scene Layout Generation via Scaled Human-aligned Data Synthesis and Multi-Stage Preference Optimization

Perception-R1: Advancing Multimodal Reasoning Capabilities of MLLMs via Visual Perception Reward

AS-ASR: A Lightweight Framework for Aphasia-Specific Automatic Speech Recognition

LLMs Can Compensate for Deficiencies in Visual Representations

Spatial Understanding from Videos: Structured Prompts Meet Simulation Data

Emergent Abilities of Large Language Models under Continued Pretraining for Language Adaptation

Cross-Attention Speculative Decoding

Beyond Linear Steering: Unified Multi-Attribute Control for Language Models

Noise-Robustness Through Noise: Asymmetric LoRA Adaption with Poisoning Expert

SEMMA: A Semantic Aware Knowledge Graph Foundation Model

AmpleHate: Amplifying the Attention for Versatile Implicit Hate Detection

Fairness-in-the-Workflow: How Machine Learning Practitioners at Big Tech Companies Approach Fairness in Recommender Systems

GRE Suite: Geo-localization Inference via Fine-Tuned Vision-Language Models and Enhanced Reasoning Chains

A Survey of Large Language Models for Data Challenges in Graphs

CLEAR: A Clinically-Grounded Tabular Framework for Radiology Report Evaluation

Creative Preference Optimization

MUG-Eval: A Proxy Evaluation Framework for Multilingual Generation Capabilities in Any Language

Search and Refine During Think: Facilitating Knowledge Refinement for Improved Retrieval-Augmented Reasoning

Space Group Equivariant Crystal Diffusion

Schreier-Coset Graph Propagation

Examining Deployment and Refinement of the VIOLA-AI Intracranial Hemorrhage Model Using an Interactive NeoMedSys Platform

StreamBridge: Turning Your Offline Video Large Language Model into a Proactive Streaming Assistant

ConCISE: Confidence-guided Compression in Step-by-step Efficient Reasoning

AttentionDrop: A Novel Regularization Method for Transformer Models

MigGPT: Harnessing Large Language Models for Automated Migration of Out-of-Tree Linux Kernel Patches Across Versions

Hybrid Temporal Differential Consistency Autoencoder for Efficient and Sustainable Anomaly Detection in Cyber-Physical Systems

Who is Responsible When AI Fails? Mapping Causes, Entities, and Consequences of AI Privacy and Ethical Incidents

No Black Box Anymore: Demystifying Clinical Predictive Modeling with Temporal-Feature Cross Attention Mechanism

Negotiative Alignment: Embracing Disagreement to Achieve Fairer Outcomes - Insights from Urban Studies

MT-RewardTree: A Comprehensive Framework for Advancing LLM-Based Machine Translation via Reward Modeling

Pruning the Paradox: How CLIP's Most Informative Heads Enhance Performance While Amplifying Bias

KatFishNet: Detecting LLM-Generated Korean Text through Linguistic Feature Analysis

SuPreME: A Supervised Pre-training Framework for Multimodal ECG Representation Learning

Sparsity May Be All You Need: Sparse Random Parameter Adaptation

Neural Networks for Learnable and Scalable Influence Estimation of Instruction Fine-Tuning Data

"It Felt Like I Was Left in the Dark": Exploring Information Needs and Design Opportunities for Family Caregivers of Older Adult Patients in Critical Care Settings

Gradient Alignment in Physics-informed Neural Networks: A Second-Order Optimization Perspective

Advances in Multimodal Adaptation and Generalization: From Traditional Approaches to Foundation Models

A Layered Multi-Expert Framework for Long-Context Mental Health Assessments

Efficient Real-time Refinement of Language Model Text Generation

FLOAT: Generative Motion Latent Flow Matching for Audio-driven Talking Portrait

Dynamic Neural Curiosity Enhances Learning Flexibility for Autonomous Goal Discovery

Bayesian Concept Bottleneck Models with LLM Priors

G2D2: Gradient-Guided Discrete Diffusion for Inverse Problem Solving

SeCodePLT: A Unified Platform for Evaluating the Security of Code GenAI

DiRW: Path-Aware Digraph Learning for Heterophily

Towards Interactive and Learnable Cooperative Driving Automation: a Large Language Model-Driven Decision-Making Framework

DynamicNER: A Dynamic, Multilingual, and Fine-Grained Dataset for LLM-based Named Entity Recognition

CrackSCF: Lightweight Cascaded Fusion Network for Robust and Efficient Structural Crack Segmentation

ConfReady: A RAG based Assistant and Dataset for Conference Checklist Responses

FOVAL: Calibration-Free and Subject-Invariant Fixation Depth Estimation Across Diverse Eye-Tracking Datasets

Assessing invariance to affine transformations in image quality metrics

The Great AI Witch Hunt: Reviewers Perception and (Mis)Conception of Generative AI in Research Writing

Database-Augmented Query Representation for Information Retrieval

Two Is Better Than One: Aligned Representation Pairs for Anomaly Detection

BBScoreV2: Learning Time-Evolution and Latent Alignment from Stochastic Representation

Beyond Pixels: Enhancing LIME with Hierarchical Features and Segmentation Foundation Models

Spatio-Temporal Anomaly Detection with Graph Networks for Data Quality Monitoring of the Hadron Calorimeter

Understanding AI Evaluation Patterns: How Different GPT Models Assess Vision-Language Descriptions

Online Robust Planning under Model Uncertainty: A Sample-Based Approach

HiPhO: How Far Are (M)LLMs from Humans in the Latest High School Physics Olympiad Benchmark?

Noise-Robustness Through Noise: Asymmetric LoRA Adaption with Poisoning Expert

Created by

Haebom

作者

Zhaokun Wang, Jinyu Guo, Jingwen Pu, Lingfeng Chen, Hongli Pu, Jie Ou, Libo Qin, Wenhong Tian

概要

この論文は、事前訓練された言語モデルをサブタスクに適用するパラメータ効率的な微調整方法がノイズデータの干渉に対して脆弱であるという問題を解決するために、非対称LoRA poisoning experts（LoPE）という新しいフレームワークを提案します。 LoPEは、ミックスエキスパートのアーキテクチャからインスピレーションを得て、専用のポイソンリングエクスペリエンスを非対称LoRA構成に戦略的に統合します。 2段階のプロセスにより、微調整中にポイゾニングエキスパートにノイズを注入してノイズの識別と処理能力を向上させ、推論時にはそのエキスパートを選択的にマスキングして精製された知識を活用してノイズに強靭な出力を生成します。データを精製することなく、安価なノイズ注入だけで強力な性能と強靭性を達成することを実験を通して示しています。

Takeaways、Limitations

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Takeaways：

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既存のノイズ処理方法（データ前処理またはモデルアーキテクチャ修正）の限界を克服し、安価なノイズ注入だけでノイズに強靭なモデルを学習できる新しい方法提示。

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データ精製プロセスを必要とせず、時間とリソースを節約できます。

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混合エキスパートアーキテクチャとLoRAを効果的に組み合わせて、パラメータ効率を維持しながらパフォーマンスを向上させます。

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Limitations：

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LoPEの効果は、注入されるノイズの種類と量によって異なります。最適ノイズ注入戦略のさらなる研究が必要

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提案された方法がすべての種類のノイズデータに対して同じレベルの強靭性を保証するかどうかの追加の実験と分析の必要性。

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さまざまなサブタスクと言語モデルの一般化パフォーマンス検証が必要です。

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