Daily Arxiv

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CLOVER: Closed-Loop Value Estimation and Ranking for End-to-End Autonomous Driving Planning

Logging Policy Design for Off-Policy Evaluation

TFGN: Task-Free, Replay-Free Continual Pre-Training Without Catastrophic Forgetting at LLM Scale

Unlocking Complex Visual Generation via Closed-Loop Verified Reasoning

Do Coding Agents Understand Least-Privilege Authorization?

Does RAG Know When Retrieval Is Wrong? Diagnosing Context Compliance under Knowledge Conflict

Agentic Recommender System with Hierarchical Belief-State Memory

Beyond Binary: Reframing GUI Critique as Continuous Semantic Alignment

ICED: Concept-level Machine Unlearning via Interpretable Concept Decomposition

Active Learners as Efficient PRP Rerankers

PanoWorld: Towards Spatial Supersensing in 360$^\circ$ Panorama World

Protocol-Driven Development: Governing Generated Software Through Invariants and Continuous Evidence

Controllable Quantum Memory Capacity in Quantum Reservoir Networks with Tunable partial-SWAPs

ODRPO: Ordinal Decompositions of Discrete Rewards for Robust Policy Optimization

Representing Higher-Order Networks: A Survey of Graph-Based Frameworks

Beyond GRPO and On-Policy Distillation: An Empirical Sparse-to-Dense Reward Principle for Language-Model Post-Training

Fill the GAP: A Granular Alignment Paradigm for Visual Reasoning in Multimodal Large Language Models

SURGE: Surrogate Gradient Adaptation in Binary Neural Networks

BEACON: A Multimodal Dataset for Learning Behavioral Fingerprints from Gameplay Data

HYPERPOSE: Hyperbolic Kinematic Phase-Space Attention for 3D Human Pose Estimation

Swarm Skills: A Portable, Self-Evolving Multi-Agent System Specification for Coordination Engineering

Key-Value Means: Transformers with Expandable Block-Recurrent Compressed Memory

Sparsity Moves Computation: How FFN Architecture Reshapes Attention in Small Transformers

ShadowMerge: A Novel Poisoning Attack on Graph-Based Agent Memory via Relation-Channel Conflicts

Fitting Is Not Enough: Smoothness in Extremely Quantized LLMs

AIPO: Learning to Reason from Active Interaction

When Language Overwrites Vision: Over-Alignment and Geometric Debiasing in Vision-Language Models

PerFlow: Physics-Embedded Rectified Flow for Efficient Reconstruction and Uncertainty Quantification of Spatiotemporal Dynamics

BFORE: Butterfly-Firefly Optimized Retinex Enhancement for Low-Light Image Quality Improvement

Trojan Hippo: Weaponizing Agent Memory for Data Exfiltration

Skills as Verifiable Artifacts: A Trust Schema and a Biconditional Correctness Criterion for Human-in-the-Loop Agent Runtimes

Graph Construction and Matching for Imperative Programs using Neural and Structural Methods

CAP: Controllable Alignment Prompting for Unlearning in LLMs

Region-Grounded Report Generation for 3D Medical Imaging: A Fine-Grained Dataset and Graph-Enhanced Framework

DPrivBench: Benchmarking LLMs' Reasoning for Differential Privacy

Don't Retrieve, Navigate: Distilling Enterprise Knowledge into Navigable Agent Skills for QA and RAG

Hardware Utilization and Inference Performance of Edge Object Detection Under Fault Injection

KV Cache Offloading for Context-Intensive Tasks

DMax: Aggressive Parallel Decoding for dLLMs

Convergent Representations of Linguistic Constructions in Human and Artificial Neural Systems

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization

IndicSafe: A Benchmark for Evaluating Multilingual LLM Safety in South Asia

FormulaCode: Evaluating Agentic Optimization on Large Codebases

Topology-Preserving Polygon Augmentation for Segmentation in Structured Visual Domains

A Unified View of Score-Based and Drifting Models

Stock Market Prediction Using Node Transformer Architecture Integrated with BERT Sentiment Analysis

Benchmark of Benchmarks: Unpacking Influence and Code Repository Quality in LLM Safety Benchmarks

Flowette: Flow Matching with Graphette Priors for Graph Generation

Brain-OF: An Omnifunctional Foundation Model for fMRI, EEG and MEG

Long Range Frequency Tuning for QML

Golden Layers and Where to Find Them: Improved Knowledge Editing for Large Language Models Via Layer Gradient Analysis

OmniVL-Guard: Towards Unified Vision-Language Forgery Detection and Grounding via Balanced RL

Improve Large Language Model Systems with User Logs

Antidistillation Fingerprinting

Decouple Searching from Training: Scaling Data Mixing via Model Merging for Large Language Model Pre-training

ExplainerPFN: Towards tabular foundation models for model-free zero-shot feature importance estimations

"Unlimited Realm of Exploration and Experimentation": Methods and Motivations of AI-Generated Sexual Content Creators

Structure-BiEval: A Self-Supervised, Dual-Track Framework for Decoupling Structure and Content in LLM Evaluation for Web Information Systems

SafeGPT: Preventing Data Leakage and Unethical Outputs in Enterprise LLM Use

LASER: Language Model Regression for Semi-Structured Workflow Resource and Runtime Estimation

EMFusion: An Uncertainty-Aware Conditional Diffusion Framework for Frequency-Selective EMF Forecasting in Wireless Networks

Drawback of Enforcing Equivariance and its Compensation via the Lens of Expressive Power

Neural Policy Composition from Free Energy Minimization

HAI-Eval: Measuring Human-AI Synergy in Collaborative Coding

Two-Dimensional Quantization for Geometry-Aware Audio Coding

Polynomial Neural Sheaf Diffusion: A Spectral Filtering Approach on Cellular Sheaves

LLM-EDT: Large Language Model Enhanced Cross-domain Sequential Recommendation with Dual-phase Training

DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research

Sufficient Explanations in Databases and their Connections to Database Repairs

Weight Concentration Regularization for Improving Pruning Robustness Under High Sparsity

SemanticOpt: Towards LLM-Based Semantic Black-Box Optimization

Monotone and Separable Set Functions: Characterizations and Neural Models

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery

A Model Can Help Itself: Reward-Free Self-Training for LLM Reasoning

ADMIT: Few-shot Knowledge Poisoning Attacks on RAG-based Fact Checking

UniShield: An Adaptive Multi-Agent Framework for Unified Forgery Image Detection and Localization

SAE-RNA: A Sparse Autoencoder Model for Interpreting RNA Language Model Representations

How to Train Your Advisor: Steering Black-Box LLMs with Advisor Models

NoiseShift: Resolution-Aware Noise Recalibration for Better Low-Resolution Image Generation

BioBlobs: Unsupervised Discovery of Functional Substructures for Protein Function Prediction

Dynamic-TreeRPO: Breaking the Independent Trajectory Bottleneck with Structured Sampling

Painless Activation Steering: An Automated, Lightweight Approach for Post-Training Large Language Models

Logic of Hypotheses: from Zero to Full Knowledge in Neurosymbolic Integration

Autoguided Online Data Curation for Diffusion Model Training

CUBE: Contrastive Understanding by Balanced Experiments

Generalized Policy Gradient with History-Aware Decision Transformer for Reliable Routing over Graph Signals

Beyond Binary Rewards: Training LMs to Reason About Their Uncertainty

CIS-BWE: Chaos-Informed Speech Bandwidth Extension

A Scalable Multi-LLM Collaboration System with Retrieval-based Selection and Exploration-Exploitation-Driven Enhancement

Blending Supervised and Reinforcement Fine-Tuning with Prefix Sampling

Deep Double Q-learning

The Hardness of Achieving Impact in AI for Social Impact Research: A Ground-Level View of Challenges & Opportunities

FAR: Function-preserving Attention Replacement for IMC-friendly Inference

ActiveDPO: Active Direct Preference Optimization for Sample-Efficient Alignment

COCO-Inpaint: A Benchmark for Detecting and Localizing Inpainting-Based Image Manipulations

Optimizing LLM Inference: Fluid-Guided Online Scheduling with Memory Constraints

Large Language Models Could Be Rote Learners

Do Chinese models speak Chinese languages?

TokenButler: Token Importance is Predictable

Seeing is Understanding: Unlocking Causal Attention into Modality-Mutual Attention for Multimodal LLMs

Neuroevolution of Self-Attention Over Proto-Objects

Created by

Haebom

저자

Rafael C. Pinto, Anderson R. Tavares

개요

본 논문은 기존의 직사각형 패치 기반 어텐션 메커니즘 대신 시각적 특징을 공유하는 영역인 프로토-객체(proto-object)를 활용한 새로운 어텐션 메커니즘을 제안합니다. 이미지 분할을 통해 고차원 특징을 프로토-객체 단위로 처리함으로써, 고정된 패치보다 적은 수의 프로토-객체로 이미지를 분해하고 각 프로토-객체를 압축된 특징 벡터로 효율적으로 인코딩합니다. 이를 통해 더 작고 효율적인 셀프-어텐션 모듈을 구현하여 풍부한 의미 정보를 처리할 수 있습니다. 실험 결과, 패치 기반 방법 대비 62% 적은 파라미터와 2.6배 빠른 훈련 시간으로 동등하거나 더 우수한 성능을 달성함을 보여줍니다.