Daily Arxiv

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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論文の著作権は著者および関連機関にあり、共有する際は出典を明記してください。

SACL: Understanding and Combating Textual Bias in Code Retrieval with Semantic-Augmented Reranking and Localization

Towards Provable (In)Secure Model Weight Release Schemes

Semantic Scene Graph for Ultrasound Image Explanation and Scanning Guidance

IndieFake Dataset: A Benchmark Dataset for Audio Deepfake Detection

These Are Not All the Features You Are Looking For: A Fundamental Bottleneck in Supervised Pretraining

In-Context Learning Strategies Emerge Rationally

Fake it till You Make it: Reward Modeling as Discriminative Prediction

Semantic Preprocessing for LLM-based Malware Analysis

PCDVQ: Enhancing Vector Quantization for Large Language Models via Polar Coordinate Decoupling

TracLLM: A Generic Framework for Attributing Long Context LLMs

TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species Generation

Composite Flow Matching for Reinforcement Learning with Shifted-Dynamics Data

Explainability of Large Language Models using SMILE: Statistical Model-agnostic Interpretability with Local Explanations

Thinkless: LLM Learns When to Think

A3: an Analytical Low-Rank Approximation Framework for Attention

Search and Refine During Think: Autonomous Retrieval-Augmented Reasoning of LLMs

JointDiT: Enhancing RGB-Depth Joint Modeling with Diffusion Transformers

Energy Matching: Unifying Flow Matching and Energy-Based Models for Generative Modeling

AI-Driven Sentiment Analytics: Unlocking Business Value in the E-Commerce Landscape

Towards Adaptive Memory-Based Optimization for Enhanced Retrieval-Augmented Generation

AirCache: Activating Inter-modal Relevancy KV Cache Compression for Efficient Large Vision-Language Model Inference

Will LLMs be Professional at Fund Investment? DeepFund: A Live Arena Perspective

Revealing higher-order neural representations of uncertainty with the Noise Estimation through Reinforcement-based Diffusion (NERD) model

Zero-TIG: Temporal Consistency-Aware Zero-Shot Illumination-Guided Low-light Video Enhancement

PP-DocBee: Improving Multimodal Document Understanding Through a Bag of Tricks

CREStE: Scalable Mapless Navigation with Internet Scale Priors and Counterfactual Guidance

Markets with Heterogeneous Agents: Dynamics and Survival of Bayesian vs. No-Regret Learners

Reward-Guided Speculative Decoding for Efficient LLM Reasoning

UP-VLA: A Unified Understanding and Prediction Model for Embodied Agent

DisCoPatch: Taming Adversarially-driven Batch Statistics for Improved Out-of-Distribution Detection

Materialist: Physically Based Editing Using Single-Image Inverse Rendering

Representation Learning of Lab Values via Masked AutoEncoders

Lagrangian Index Policy for Restless Bandits with Average Reward

SIDA: Social Media Image Deepfake Detection, Localization and Explanation with Large Multimodal Model

InfiniCube: Unbounded and Controllable Dynamic 3D Driving Scene Generation with World-Guided Video Models

Pretrained Reversible Generation as Unsupervised Visual Representation Learning

MvKeTR: Chest CT Report Generation with Multi-View Perception and Knowledge Enhancement

GASP: Efficient Black-Box Generation of Adversarial Suffixes for Jailbreaking LLMs

ToolScan: A Benchmark for Characterizing Errors in Tool-Use LLMs

Recall and Refine: A Simple but Effective Source-free Open-set Domain Adaptation Framework

InterFormer: Effective Heterogeneous Interaction Learning for Click-Through Rate Prediction

Prompting with Phonemes: Enhancing LLMs' Multilinguality for Non-Latin Script Languages

Advanced computer vision for extracting georeferenced vehicle trajectories from drone imagery

Rapid Gyroscope Calibration: A Deep Learning Approach

HERMES: temporal-coHERent long-forM understanding with Episodes and Semantics

A GREAT Architecture for Edge-Based Graph Problems Like TSP

ClimateIQA: A New Dataset and Benchmark to Advance Vision-Language Models in Meteorology Anomalies Analysis

MockLLM: A Multi-Agent Behavior Collaboration Framework for Online Job Seeking and Recruiting

Is my Data in your AI Model? Membership Inference Test with Application to Face Images

PuriDefense: Randomized Local Implicit Adversarial Purification for Defending Black-box Query-based Attacks

Continual Learning as Computationally Constrained Reinforcement Learning

Efficient Image Generation with Variadic Attention Heads

Smart Ride and Delivery Services with Electric Vehicles: Leveraging Bidirectional Charging for Profit Optimisation

From Memories to Maps: Mechanisms of In-Context Reinforcement Learning in Transformers

Graphs Meet AI Agents: Taxonomy, Progress, and Future Opportunities

Taming the Untamed: Graph-Based Knowledge Retrieval and Reasoning for MLLMs to Conquer the Unknown

Exploring Big Five Personality and AI Capability Effects in LLM-Simulated Negotiation Dialogues

Doppelganger Method: Breaking Role Consistency in LLM Agent via Prompt-based Transferable Adversarial Attack

Metis-RISE: RL Incentivizes and SFT Enhances Multimodal Reasoning Model Learning

Fast Monte Carlo Tree Diffusion: 100x Speedup via Parallel Sparse Planning

NFISiS: New Perspectives on Fuzzy Inference Systems for Renewable Energy Forecasting

The State of Large Language Models for African Languages: Progress and Challenges

Structuring the Unstructured: A Multi-Agent System for Extracting and Querying Financial KPIs and Guidance

Super Co-alignment for Sustainable Symbiotic Society

Improving Human-AI Coordination through Online Adversarial Training and Generative Models

WiS Platform: Enhancing Evaluation of LLM-Based Multi-Agent Systems Through Game-Based Analysis

Review learning: Real world validation of privacy preserving continual learning across medical institutions

Whole-Body Conditioned Egocentric Video Prediction

MTSBench: Benchmarking Multivariate Time Series Anomaly Detection and Model Selection at Scale

HalluSegBench: Counterfactual Visual Reasoning for Segmentation Hallucination Evaluation

WorldVLA: Towards Autoregressive Action World Model

"What's Up, Doc?": Analyzing How Users Seek Health Information in Large-Scale Conversational AI Datasets

Potemkin Understanding in Large Language Models

SkLEP: A Slovak General Language Understanding Benchmark

Process mining-driven modeling and simulation to enhance fault diagnosis in cyber-physical systems

TITAN: Query-Token based Domain Adaptive Adversarial Learning

SmoothSinger: A Conditional Diffusion Model for Singing Voice Synthesis with Multi-Resolution Architecture

Optimising 4th-Order Runge-Kutta Methods: A Dynamic Heuristic Approach for Efficiency and Low Storage

Domain Knowledge-Enhanced LLMs for Fraud and Concept Drift Detection

Scalable Bayesian Low-Rank Adaptation of Large Language Models via Stochastic Variational Subspace Inference

Leveraging LLM-Assisted Query Understanding for Live Retrieval-Augmented Generation

Temporal-Aware Graph Attention Network for Cryptocurrency Transaction Fraud Detection

Pay Attention to Small Weights

Real-time and personalized product recommendations for large e-commerce platforms

RQdia: Regularizing Q-Value Distributions With Image Augmentation

CA-I2P: Channel-Adaptive Registration Network with Global Optimal Selection

A Systematic Review of Human-AI Co-Creativity

Holistic Surgical Phase Recognition with Hierarchical Input Dependent State Space Models

On Uniform Weighted Deep Polynomial approximation

Exploring Adapter Design Tradeoffs for Low Resource Music Generation

Detecting Referring Expressions in Visually Grounded Dialogue with Autoregressive Language Models

Small Encoders Can Rival Large Decoders in Detecting Groundedness

Hyperspherical Variational Autoencoders Using Efficient Spherical Cauchy Distribution

Integrating Vehicle Acoustic Data for Enhanced Urban Traffic Management: A Study on Speed Classification in Suzhou

DiLoCoX: A Low-Communication Large-Scale Training Framework for Decentralized Cluster

Agent-RewardBench: Towards a Unified Benchmark for Reward Modeling across Perception, Planning, and Safety in Real-World Multimodal Agents

From On-chain to Macro: Assessing the Importance of Data Source Diversity in Cryptocurrency Market Forecasting

$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models

BitMark for Infinity: Watermarking Bitwise Autoregressive Image Generative Models

Task-Aware KV Compression For Cost-Effective Long Video Understanding

Revealing higher-order neural representations of uncertainty with the Noise Estimation through Reinforcement-based Diffusion (NERD) model

Created by

Haebom

作者

Hojjat Azimi Asrari, Megan AK Peters

概要

本論文は、観察者の環境（内容や構造）をエンコードする「一次表象（FOR）」ではなく、「一次表象」に対するもの（例：強度や不確実性）を示す「高次表象（HOR）」に焦点を当てます。特に、不確実性に対する高次表象は、一次表象の特徴を直接反映するのではなく、不確実性に対する事前期待を含むノイズの多い推定プロセスを反映しています。この研究は、人間の被験者が意図的に標的神経パターンを生成するように学習する「復号されたニューロフィードバック」課題の神経データを使用して、「雑音期待」高次表象を研究する。強化学習ベースの拡散によるノイズ推定（NERD）モデルを開発し、脳がこのプロセスを実行する方法を特徴付け、NERDモデルが人間の行動に高い説明力を提供することを示しています。

Takeaways、Limitations

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Takeaways：脳が自分の雑音の学習をどのように実行するかについての新しいモデル（NERD）を提示し、復号されたニューロフィードバックの課題を通じてその妥当性を検証しました。高次表象、特に不確実性に対する高次表象の神経機構の理解に寄与する。

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Limitations： NERDモデルは特定の課題（復号化されたニューロフィードバック）に適用され、他の種類のノイズや不確実性の推定課題にも適用できるかどうかをさらに検討する必要があります。モデルの一般化の可能性と生物学的妥当性のさらなる検証が必要です。人間の脳のノイズ推定プロセスの完全な説明を提供するものではありません。

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