haebom
Daily Arxiv
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A Theoretical Framework for Environmental Similarity and Vessel Mobility as Coupled Predictors of Marine Invasive Species Pathways
CareMedEval dataset: Evaluating Critical Appraisal and Reasoning in the Biomedical Field
Node-Based Editing for Multimodal Generation of Text, Audio, Image, and Video
Control Barrier Function for Aligning Large Language Models
A Criminology of Machines
FATE: A Formal Benchmark Series for Frontier Algebra of Multiple Difficulty Levels
PoCo: Agentic Proof-of-Concept Exploit Generation for Smart Contracts
Causal Graph Neural Networks for Healthcare
LA-MARRVEL: A Knowledge-Grounded and Language-Aware LLM Reranker for AI-MARRVEL in Rare Disease Diagnosis
OceanAI: A Conversational Platform for Accurate, Transparent, Near-Real-Time Oceanographic Insights
Pay for The Second-Best Service: A Game-Theoretic Approach Against Dishonest LLM Providers
Artificial Intelligence in Elementary STEM Education: A Systematic Review of Current Applications and Future Challenges
Non-Convex Over-the-Air Heterogeneous Federated Learning: A Bias-Variance Trade-off
TraceTrans: Translation and Spatial Tracing for Surgical Prediction
TowerVision: Understanding and Improving Multilinguality in Vision-Language Models
Gestura: A LVLM-Powered System Bridging Motion and Semantics for Real-Time Free-Form Gesture Understanding
ADPO: Anchored Direct Preference Optimization
Rewarding the Journey, Not Just the Destination: A Composite Path and Answer Self-Scoring Reward Mechanism for Test-Time Reinforcement Learning
RealDPO: Real or Not Real, that is the Preference
Deep Edge Filter: Return of the Human-Crafted Layer in Deep Learning
Mathematics with large language models as provers and verifiers
Integrating Sequential and Relational Modeling for User Events: Datasets and Prediction Tasks
A Systematic Evaluation of Self-Supervised Learning for Label-Efficient Sleep Staging with Wearable EEG
Learning to Navigate Socially Through Proactive Risk Perception
Training Large Language Models To Reason In Parallel With Global Forking Tokens
ChessArena: A Chess Testbed for Evaluating Strategic Reasoning Capabilities of Large Language Models
HyperAdapt: Simple High-Rank Adaptation
Comparing Computational Pathology Foundation Models using Representational Similarity Analysis
Back to Ear: Perceptually Driven High Fidelity Music Reconstruction
Test-Time Warmup for Multimodal Large Language Models
Zero-Shot Referring Expression Comprehension via Vison-Language True/False Verification
Memorization in Large Language Models in Medicine: Prevalence, Characteristics, and Implications
Balancing Quality and Variation: Spam Filtering Distorts Data Label Distributions
A Multi-target Bayesian Transformer Framework for Predicting Cardiovascular Disease Biomarkers during Pandemics
Med-GLIP: Advancing Medical Language-Image Pre-training with Large-scale Grounded Dataset
NyayaRAG: Realistic Legal Judgment Prediction with RAG under the Indian Common Law System
XRoboToolkit: A Cross-Platform Framework for Robot Teleoperation
Vibe Coding as a Reconfiguration of Intent Mediation in Software Development: Definition, Implications, and Research Agenda
GENIAL: Generative Design Space Exploration via Network Inversion for Low Power Algorithmic Logic Units
MeAJOR Corpus: A Multi-Source Dataset for Phishing Email Detection
Deep Graph Learning for Industrial Carbon Emission Analysis and Policy Impact
Towards Efficient and Accurate Spiking Neural Networks via Adaptive Bit Allocation
Advanced Sign Language Video Generation with Compressed and Quantized Multi-Condition Tokenization
HoliSafe: Holistic Safety Benchmarking and Modeling for Vision-Language Model
Explicit Density Approximation for Neural Implicit Samplers Using a Bernstein-Based Convex Divergence
HELM: Hyperbolic Large Language Models via Mixture-of-Curvature Experts
Reasoning Models Hallucinate More: Factuality-Aware Reinforcement Learning for Large Reasoning Models
Composite Flow Matching for Reinforcement Learning with Shifted-Dynamics Data
Hierarchical Retrieval with Evidence Curation for Open-Domain Financial Question Answering on Standardized Documents
Two Causally Related Needles in a Video Haystack
Robustness in Large Language Models: A Survey of Mitigation Strategies and Evaluation Metrics
Autocomp: A Powerful and Portable Code Optimizer for Tensor Accelerators
But what is your honest answer? Aiding LLM-judges with honest alternatives using steering vectors
Learning Dynamics of RNNs in Closed-Loop Environments
Revisiting Residual Connections: Orthogonal Updates for Stable and Efficient Deep Networks
Multimodal Cancer Modeling in the Age of Foundation Model Embeddings
Benchmarking LLM Faithfulness in RAG with Evolving Leaderboards
TathyaNyaya and FactLegalLlama: Advancing Factual Judgment Prediction and Explanation in the Indian Legal Context
Quamba2: A Robust and Scalable Post-training Quantization Framework for Selective State Space Models
Efficient Model Development through Fine-tuning Transfer
SafeVLA: Towards Safety Alignment of Vision-Language-Action Model via Constrained Learning
Pragmatic Reasoning improves LLM Code Generation
KGGen: Extracting Knowledge Graphs from Plain Text with Language Models
How Memory in Optimization Algorithms Implicitly Modifies the Loss
GASP: Efficient Black-Box Generation of Adversarial Suffixes for Jailbreaking LLMs
Transferable & Stealthy Ensemble Attacks: A Black-Box Jailbreaking Framework for Large Language Models
Understanding Adam Requires Better Rotation Dependent Assumptions
Beyond the Kolmogorov Barrier: A Learnable Weighted Hybrid Autoencoder for Model Order Reduction
Residual Kolmogorov-Arnold Network for Enhanced Deep Learning
Legal Fact Prediction: The Missing Piece in Legal Judgment Prediction
LLM Targeted Underperformance Disproportionately Impacts Vulnerable Users
Projection Methods for Operator Learning and Universal Approximation
Stochastic Diffusion: A Diffusion Probabilistic Model for Stochastic Time Series Forecasting
A Unified Kernel for Neural Network Learning
Toward Autonomous Engineering Design: A Knowledge-Guided Multi-Agent Framework
SnapStream: Efficient Long Sequence Decoding on Dataflow Accelerators
Orion-MSP: Multi-Scale Sparse Attention for Tabular In-Context Learning
BOTS: A Unified Framework for Bayesian Online Task Selection in LLM Reinforcement Finetuning
Toward Clinically Grounded Foundation Models in Pathology
Seg the HAB: Language-Guided Geospatial Algae Bloom Reasoning and Segmentation
A Principle of Targeted Intervention for Multi-Agent Reinforcement Learning
Structured Debate Improves Corporate Credit Reasoning in Financial AI
Cross-modal Causal Intervention for Alzheimer's Disease Prediction
Evaluating LLM-Contaminated Crowdsourcing Data Without Ground Truth
Style2Code: A Style-Controllable Code Generation Framework with Dual-Modal Contrastive Representation Learning
Building Altruistic and Moral AI Agent with Brain-inspired Emotional Empathy Mechanisms
"Let's Agree to Disagree": Investigating the Disagreement Problem in Explainable AI for Text Summarization
Collaboration Dynamics and Reliability Challenges of Multi-Agent LLM Systems in Finite Element Analysis
Discussion Graph Semantics of First-Order Logic with Equality for Reasoning about Discussion and Argumentation
X-Diffusion: Training Diffusion Policies on Cross-Embodiment Human Demonstrations
Addressing divergent representations from causal interventions on neural networks
Integrating Temporal and Structural Context in Graph Transformers for Relational Deep Learning
LLM-as-a-Judge: Toward World Models for Slate Recommendation Systems
Are language models aware of the road not taken? Token-level uncertainty and hidden state dynamics
Alternative Fairness and Accuracy Optimization in Criminal Justice
RAGalyst: Automated Human-Aligned Agentic Evaluation for Domain-Specific RAG
Decoding Emergent Big Five Traits in Large Language Models: Temperature-Dependent Expression and Architectural Clustering
OUNLP at TSAR 2025 Shared Task: Multi-Round Text Simplifier via Code Generation
RUST-BENCH: Benchmarking LLM Reasoning on Unstructured Text within Structured Tables
Q3R: Quadratic Reweighted Rank Regularizer for Effective Low-Rank Training
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(How) Do reasoning models reason?
Created by
Haebom
저자
Subbarao Kambhampati, Kaya Stechly, Karthik Valmeekam
개요
본 논문은 OpenAI o1과 DeepSeek R1과 같은 최근 등장한 대규모 추론 모델(LRMs)에 대한 광범위하고 통합적인 관점을 제시하며, 이들의 가능성, 능력의 원천, 오해 및 한계를 포함한다.
시사점, 한계점
•
시사점:
대규모 추론 모델(LRMs)의 가능성, 능력의 원천에 대한 통합적 이해 제공
•
한계점:
구체적인 모델 분석이나 실험 결과가 부족할 가능성 (추상적인 관점 제시에 그칠 수 있음)
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