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ENSEMBITS: an alphabet of protein conformational ensembles

(How) Do Large Language Models Understand High-Level Message Sequence Charts?

Query-Conditioned Test-Time Self-Training for Large Language Models

Constitutional Governance in Metric Spaces

Inducing Overthink: Hierarchical Genetic Algorithm-based DoS Attack on Black-Box Large Language Reasoning Models

LeanSearch v2: Global Premise Retrieval for Lean 4 Theorem Proving

MLGIB: Multi-Label Graph Information Bottleneck for Expressive and Robust Message Passing

Watermarking Should Be Treated as a Monitoring Primitive

Does language matter for spoken word classification? A multilingual generative meta-learning approach

Scaling few-shot spoken word classification with generative meta-continual learning

Context Training with Active Information Seeking

WriteSAE: Sparse Autoencoders for Recurrent State

Learning, Fast and Slow: Towards LLMs That Adapt Continually

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

Detecting overfitting in Neural Networks during long-horizon grokking using Random Matrix Theory

A New Technique for AI Explainability using Feature Association Map

TokenRatio: Principled Token-Level Preference Optimization via Ratio Matching

Boosting Omni-Modal Language Models: Staged Post-Training with Visually Debiased Evaluation

GEAR: Granularity-Adaptive Advantage Reweighting for LLM Agents via Self-Distillation

Overcoming Dynamics-Blindness: Training-Free Pace-and-Path Correction for VLA Models

Predictive Maps of Multi-Agent Reasoning: A Successor-Representation Spectrum for LLM Communication Topologies

LoKA: Low-precision Kernel Applications for Recommendation Models At Scale

Prompt-Activation Duality: Improving Activation Steering via Attention-Level Interventions

Pretraining large language models with MXFP4 on Native FP4 Hardware

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

Evolutionary Ensemble of Agents

Geometrically Constrained Stenosis Editing in Coronary Angiography via Entropic Optimal Transport

AgentForesight: Online Auditing for Early Failure Prediction in Multi-Agent Systems

Trapping Attacker in Dilemma: Examining Internal Correlations and External Influences of Trigger for Defending GNN Backdoors

Normalization Equivariance for Arbitrary Backbones, with Application to Image Denoising

Flow-OPD: On-Policy Distillation for Flow Matching Models

One Token Per Frame: Reconsidering Visual Bandwidth in World Models for VLA Policy

Toward Privileged Foundation Models:LUPI for Accelerated and Improved Learning

Predict-then-Diffuse: Adaptive Response Length for Compute-Budgeted Inference in Diffusion LLMs

Motion-Aware Caching for Efficient Autoregressive Video Generation

ClawGym: A Scalable Framework for Building Effective Claw Agents

SIEVES: Selective Prediction Generalizes through Visual Evidence Scoring

Quantifying and Mitigating Self-Preference Bias of LLM Judges

Quotient-Space Diffusion Models

Image Generators are Generalist Vision Learners

RoboWM-Bench: A Benchmark for Evaluating World Models in Robotic Manipulation

Evaluating Adaptive Personalization of Educational Readings with Simulated Learners

UniMamba: A Unified Spatial-Temporal Modeling Framework with State-Space and Attention Integration

RoboLab: A High-Fidelity Simulation Benchmark for Analysis of Task Generalist Policies

ECHO: Elastic Speculative Decoding with Sparse Gating for High-Concurrency Scenarios

PinpointQA: A Dataset and Benchmark for Small Object-Centric Spatial Understanding in Indoor Videos

LLMs Should Express Uncertainty Explicitly

A Security Analysis of the OpenClaw AI Agent Framework

OneSearch-V2: The Latent Reasoning Enhanced Self-distillation Generative Search Framework

Procedural Refinement by LLM-driven Algorithmic Debugging for ARC-AGI-2

Residual Stream Duality in Modern Transformer Architectures

M$^2$RNN: Non-Linear RNNs with Matrix-Valued States for Scalable Language Modeling

Reinforcement Learning for Diffusion LLMs with Entropy-Guided Step Selection and Stepwise Advantages

TERMINATOR: Learning Optimal Exit Points for Early Stopping in Chain-of-Thought Reasoning

Adapting Dijkstra for Buffers and Unlimited Transfers

Neural Field Thermal Tomography: A Differentiable Physics Framework for Non-Destructive Evaluation

V2M-Zero: Zero-Pair Time-Aligned Video-to-Music Generation

Gradient Iterated Temporal-Difference Learning

Vibe Code Bench: Evaluating AI Models on End-to-End Web Application Development

Robometer: Scaling General-Purpose Robotic Reward Models via Trajectory Comparisons

Decoupling Stability and Plasticity for Multi-Modal Test-Time Adaptation

MPU: Towards Secure and Privacy-Preserving Knowledge Unlearning for Large Language Models

Grokking Finite-Dimensional Algebra

CUICurate: A GraphRAG-based Framework for Automated Clinical Concept Curation for NLP applications

MALLVI: A Multi-Agent Framework for Integrated Generalized Robotics Manipulation

Artificial Intelligence Specialization in the European Union: Underexplored Role of the Periphery at NUTS-3 Level

Numerical exploration of the range of shape functionals using neural networks

Finding Interpretable Prompt-Specific Circuits in Language Models

ArGEnT: Arbitrary Geometry-encoded Transformer for Operator Learning

Krause Synchronization Transformers

Proximal Action Replacement for Behavior Cloning Actor-Critic in Offline Reinforcement Learning

VLRS-Bench: A Vision-Language Reasoning Benchmark for Remote Sensing

GhostCite: A Large-Scale Analysis of Citation Validity in the Age of Large Language Models

Boosting LLM Reasoning via Human-Inspired Reward Shaping

PaAno: Patch-Based Representation Learning for Time-Series Anomaly Detection

Neural Signals Generate Clinical Notes in the Wild

L2R: Low-Rank and Lipschitz-Controlled Routing for Mixture-of-Experts

OPT-Engine: Benchmarking the Limits of LLMs in Optimization Modeling via Complexity Scaling

Teaching and Evaluating LLMs to Reason About Polymer Design Related Tasks

The Multi-View Paradigm Shift in MRI Radiomics: Predicting MGMT Methylation in Glioblastoma

LangPrecip: Language-Aware Multimodal Precipitation Nowcasting

Achieving Approximate Symmetry Is Exponentially Easier than Exact Symmetry

Why Goal-Conditioned Reinforcement Learning Works: Relation to Dual Control

AI-Driven Optimization under Uncertainty for Mineral Processing Operations

fMRI-LM: Towards a Universal Foundation Model for Language-Aligned fMRI Understanding

A cross-species neural foundation model for end-to-end speech decoding

How Learning Rate Decay Wastes Your Best Data in Curriculum-Based LLM Pretraining

Optimizing PyTorch Inference with LLM-Based Multi-Agent Systems

Chinese Short-Form Creative Content Generation via Explanation-Oriented Multi-Objective Optimization

Descriptor: Distance-Annotated Traffic Perception Question Answering (DTPQA)

Moral Susceptibility and Robustness under Persona Role-Play in Large Language Models

From Ranking to Reasoning: Explainable Web API Recommendation via Semantic Reasoning

Higher-order Linear Attention

A Tutorial on Cognitive Biases in Agentic AI-Driven 6G Autonomous Networks

Seeing Through the Brain: New Insights from Decoding Visual Stimuli with fMRI

AMiD: Knowledge Distillation for LLMs with $\alpha$-mixture Assistant Distribution

VER: Vision Expert Transformer for Robot Learning via Foundation Distillation and Dynamic Routing

TiTok: Transfer Token-level Knowledge via Contrastive Excess to Transplant LoRA

The Pitfalls of KV Cache Compression

AVEX: What Matters for Animal Vocalization Encoding

Geometry aware inference of steady state PDEs using Equivariant Neural Fields representations

Created by

Haebom

저자

Giovanni Catalani, Michael Bauerheim, Frederic Tost, Xavier Bertrand, Joseph Morlier

개요

enf2enf는 최근 제안된 Equivariant Neural Field 아키텍처를 기반으로, 매개변수화되지 않은 기하학적 변동성을 갖는 정상 상태 편미분 방정식(PDE)을 예측하기 위한 인코더-디코더 방법론입니다. 입력 기하 구조는 기하학적 근거를 유지하고 국소 현상을 포착하는 잠재 점 구름 임베딩으로 인코딩됩니다. 결과 표현은 전역 매개변수와 결합되어 연속 출력 필드로 직접 디코딩되어 기하학과 물리학 간의 결합을 효율적으로 모델링합니다. 국소성 및 병진 불변성의 귀납적 편향을 활용하여 미세한 물리적 특징과 복잡한 형태 변화를 포착하여 일반화 및 물리적 준수성을 향상시킵니다. 고충실도 공기역학 데이터 세트, 초탄성 재료 벤치마크 및 다중 요소 에어포일 기하 구조에 대한 광범위한 실험을 통해 제안된 모델이 최첨단 그래프 기반, 연산자 학습 및 신경장 방법과 비교하여 우수하거나 경쟁력 있는 성능을 달성함을 보여줍니다. 특히, 이 방법은 실시간 추론과 제로샷 초해상도를 지원하여 저해상도 메시에서 효율적인 훈련을 지원하면서 전체 규모의 이산화에 대해 높은 정확도를 유지합니다.