Daily Arxiv

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VisPlay: Self-Evolving Vision-Language Models from Images

CompTrack: Information Bottleneck-Guided Low-Rank Dynamic Token Compression for Point Cloud Tracking

Multimodal Evaluation of Russian-language Architectures

Adversarial Poetry as a Universal Single-Turn Jailbreak Mechanism in Large Language Models

OEMA: Ontology-Enhanced Multi-Agent Collaboration Framework for Zero-Shot Clinical Named Entity Recognition

Finetuning LLMs for Automatic Form Interaction on Web-Browser in Selenium Testing Framework

Kandinsky 5.0: A Family of Foundation Models for Image and Video Generation

Orion: A Unified Visual Agent for Multimodal Perception, Advanced Visual Reasoning and Execution

Can Artificial Intelligence Accelerate Technological Progress? Researchers' Perspectives on AI in Manufacturing and Materials Science

Node-Level Uncertainty Estimation in LLM-Generated SQL

Auditing Google's AI Overviews and Featured Snippets: A Case Study on Baby Care and Pregnancy

Mesh-based Super-resolution of Detonation Flows with Multiscale Graph Transformers

STAMP: Spatial-Temporal Adapter with Multi-Head Pooling

Do Not Merge My Model! Safeguarding Open-Source LLMs Against Unauthorized Model Merging

Statistically Assuring Safety of Control Systems using Ensembles of Safety Filters and Conformal Prediction

LoRA on the Go: Instance-level Dynamic LoRA Selection and Merging

CaberNet: Causal Representation Learning for Cross-Domain HVAC Energy Prediction

Kaggle Chronicles: 15 Years of Competitions, Community and Data Science Innovation

Injecting Falsehoods: Adversarial Man-in-the-Middle Attacks Undermining Factual Recall in LLMs

TabDistill: Distilling Transformers into Neural Nets for Few-Shot Tabular Classification

Diagnosing Hallucination Risk in AI Surgical Decision-Support: A Sequential Framework for Sequential Validation

GAPO: Robust Advantage Estimation for Real-World Code LLMs

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

Practical and Stealthy Touch-Guided Jailbreak Attacks on Deployed Mobile Vision-Language Agents

HiViS: Hiding Visual Tokens from the Drafter for Speculative Decoding in Vision-Language Models

Decoding Deception: Understanding Automatic Speech Recognition Vulnerabilities in Evasion and Poisoning Attacks

Interpretability as Alignment: Making Internal Understanding a Design Principle

How many patients could we save with LLM priors?

CoBA: Counterbias Text Augmentation for Mitigating Various Spurious Correlations via Semantic Triples

Interpreting the Effects of Quantization on LLMs

From Confidence to Collapse in LLM Factual Robustness

PepThink-R1: LLM for Interpretable Cyclic Peptide Optimization with CoT SFT and Reinforcement Learning

Learning to Detect Unknown Jailbreak Attacks in Large Vision-Language Models

MAQuA: Adaptive Question-Asking for Multidimensional Mental Health Screening using Item Response Theory

LLMDistill4Ads: Using Cross-Encoders to Distill from LLM Signals for Advertiser Keyphrase Recommendations

Efficient Solution and Learning of Robust Factored MDPs

To Trust or Not to Trust: On Calibration in ML-based Resource Allocation for Wireless Networks

Parallelism Meets Adaptiveness: Scalable Documents Understanding in Multi-Agent LLM Systems

HAWAII: Hierarchical Visual Knowledge Transfer for Efficient Vision-Language Models

When concept-based XAI is imprecise: Do people distinguish between generalisations and misrepresentations?

Eliciting Reasoning in Language Models with Cognitive Tools

Beyond Bias Scores: Unmasking Vacuous Neutrality in Small Language Models

From Static to Adaptive Defense: Federated Multi-Agent Deep Reinforcement Learning-Driven Moving Target Defense Against DoS Attacks in UAV Swarm Networks

Policy Search, Retrieval, and Composition via Task Similarity in Collaborative Agentic Systems

Fast-DataShapley: Neural Modeling for Training Data Valuation

An Iterative Question-Guided Framework for Knowledge Base Question Answering

A survey of using EHR as real-world evidence for discovering and validating new drug indications

CSI-Bench: A Large-Scale In-the-Wild Dataset for Multi-task WiFi Sensing

A Distributionally Robust Framework for Nuisance in Causal Effect Estimation

BanditSpec: Adaptive Speculative Decoding via Bandit Algorithms

Vector Quantized-Elites: Unsupervised and Problem-Agnostic Quality-Diversity Optimization

CaKE: Circuit-aware Editing Enables Generalizable Knowledge Learners

A Closer Look at Adversarial Suffix Learning for Jailbreaking LLMs: Augmented Adversarial Trigger Learning

CleverDistiller: Simple and Spatially Consistent Cross-modal Distillation

LLMInit: A Free Lunch from Large Language Models for Selective Initialization of Recommendation

Securing Smart Contract Languages with a Unified Agentic Framework for Vulnerability Repair in Solidity and Move

TRADES: Generating Realistic Market Simulations with Diffusion Models

Recent Advances in Discrete Speech Tokens: A Review

Oracular Programming: A Modular Foundation for Building LLM-Enabled Software

KVTuner: Sensitivity-Aware Layer-Wise Mixed-Precision KV Cache Quantization for Efficient and Nearly Lossless LLM Inference

RAPID: Robust and Agile Planner Using Inverse Reinforcement Learning for Vision-Based Drone Navigation

OmniThink: Expanding Knowledge Boundaries in Machine Writing through Thinking

Efficient Architectures for High Resolution Vision-Language Models

MMVA: Multimodal Matching Based on Valence and Arousal across Images, Music, and Musical Captions

Automatically Detecting Online Deceptive Patterns

LEARNER: Contrastive Pretraining for Learning Fine-Grained Patient Progression from Coarse Inter-Patient Labels

Atomic Calibration of LLMs in Long-Form Generations

TopoTune : A Framework for Generalized Combinatorial Complex Neural Networks

Asymptotic and Finite Sample Analysis of Nonexpansive Stochastic Approximations with Markovian Noise

Introducing DEFORMISE: A deep learning framework for dementia diagnosis in the elderly using optimized MRI slice selection

KWT-Tiny: RISC-V Accelerated, Embedded Keyword Spotting Transformer

Provably Robust Pre-Trained Ensembles for Biomarker-Based Cancer Classification

DiffuSyn Bench: Evaluating Vision-Language Models on Real-World Complexities with Diffusion-Generated Synthetic Benchmarks

Property-guided Inverse Design of Metal-Organic Frameworks Using Quantum Natural Language Processing

Can LLMs Replace Economic Choice Prediction Labs? The Case of Language-based Persuasion Games

LSAP: Rethinking Inversion Fidelity, Perception and Editability in GAN Latent Space

As If We've Met Before: LLMs Exhibit Certainty in Recognizing Seen Files

SafeRBench: A Comprehensive Benchmark for Safety Assessment in Large Reasoning Models

Benchmarking Multi-Step Legal Reasoning and Analyzing Chain-of-Thought Effects in Large Language Models

Multi-dimensional Data Analysis and Applications Basing on LLM Agents and Knowledge Graph Interactions

Towards Efficient Multimodal Unified Reasoning Model via Model Merging

FATHOMS-RAG: A Framework for the Assessment of Thinking and Observation in Multimodal Systems that use Retrieval Augmented Generation

Probing the Critical Point (CritPt) of AI Reasoning: a Frontier Physics Research Benchmark

Evaluating Multimodal Large Language Models with Daily Composite Tasks in Home Environments

Taming Uncertainty via Automation: Observing, Analyzing, and Optimizing Agentic AI Systems

Constraint-Guided Prediction Refinement via Deterministic Diffusion Trajectories

The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity

PoE-World: Compositional World Modeling with Products of Programmatic Experts

Bridging the Gap in XAI-Why Reliable Metrics Matter for Explainability and Compliance

Dataset Distillation for Pre-Trained Self-Supervised Vision Models

Thinking-while-Generating: Interleaving Textual Reasoning throughout Visual Generation

Taming the Long-Tail: Efficient Reasoning RL Training with Adaptive Drafter

Dexterity from Smart Lenses: Multi-Fingered Robot Manipulation with In-the-Wild Human Demonstrations

Teacher-Guided One-Shot Pruning via Context-Aware Knowledge Distillation

Evolution Strategies at the Hyperscale

Faster Certified Symmetry Breaking Using Orders With Auxiliary Variables

Stabilizing Policy Gradient Methods via Reward Profiling

SAM 3D: 3Dfy Anything in Images

Improving Long-Tailed Object Detection with Balanced Group Softmax and Metric Learning

Generative AI for Enhanced Wildfire Detection: Bridging the Synthetic-Real Domain Gap

Faster Certified Symmetry Breaking Using Orders With Auxiliary Variables

Created by

Haebom

저자

Markus Anders, Bart Bogaerts, Benjamin Bog{\o}, Arthur Gontier, Wietze Koops, Ciaran McCreesh, Magnus O. Myreen, Jakob Nordstrom, Andy Oertel, Adrian Rebola-Pardo, Yong Kiam Tan

개요

본 논문은 조합 문제 해결에서 중요한 기법인 대칭성 파괴의 올바른 구현을 보장하는 방법을 제시한다. 특히, 해를 출력할 뿐만 아니라 표준 형식의 정확성 증명을 제공하는 인증 솔버를 구축하는 데 초점을 맞춘다. 기존의 대칭성 추론을 증명에 포함시키는 효율적인 방법을 개발하는 것은 오랜 과제였으며, 본 연구에서는 보조 변수를 사용하여 순서를 인코딩하는 새로운 방법을 제안한다. 이를 통해 대규모 대칭성에 적합하고, 기존 방법보다 훨씬 빠른 속도를 낼 수 있다. SAT 대칭성 파괴에 대한 실험을 통해 성능 향상을 입증한다.

시사점, 한계점

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시사점:

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대칭성 파괴를 위한 효율적인 증명 로깅 및 검증 방법 제시

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보조 변수를 활용한 순서 인코딩 기법 제안, 기존 방법 대비 성능 향상

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실험을 통해 제안된 방법의 유효성 검증

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한계점:

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구체적인 한계점은 논문에 명시되지 않음 (추후 연구 필요)

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