3d ago
Generate Then Correct: Single Shot Global Correction for Aspect Sentiment Quad Prediction
Generates then corrects predictions for aspect sentiment quad prediction in fine-grained opinion mining tasks.
3d ago
Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving
Proposes parallel framework combining imitation and reinforcement learning for end-to-end autonomous driving instead of sequential fine-tuning.
3d ago
Causal Discovery in Action: Learning Chain-Reaction Mechanisms from Interventions
Studies causal discovery in chain-reaction dynamical systems using interventional data with identifiability guarantees.
3d ago
Unilateral Relationship Revision Power in Human-AI Companion Interaction
Philosophical analysis of moral dimensions in human-AI companion interactions and provider control structures.
3d ago
Large Language Model Guided Incentive Aware Reward Design for Cooperative Multi-Agent Reinforcement Learning
Framework using LLMs to automatically synthesize reward programs for cooperative multi-agent reinforcement learning systems.
3d ago
TIGFlow-GRPO: Trajectory Forecasting via Interaction-Aware Flow Matching and Reward-Guided Optimization
Combines flow matching with reward optimization for trajectory forecasting in autonomous driving and crowd surveillance scenarios.
3d ago
MuDD: A Multimodal Deception Detection Dataset and GSR-Guided Progressive Distillation for Non-Contact Deception Detection
Proposes multimodal deception detection dataset using GSR-guided distillation to improve non-contact deception detection.
3d ago
Beyond Code Snippets: Benchmarking LLMs on Repository-Level Question Answering
Introduces StackRepoQA, a repository-level QA benchmark for evaluating LLMs on multi-file program comprehension tasks beyond isolated code snippets.
3d ago
Toward Evaluation Frameworks for Multi-Agent Scientific AI Systems
Analyzes challenges in benchmarking multi-agent scientific AI systems, including reasoning vs retrieval, data contamination, ground truth, tool use, and reproducibility in evolving knowledge bases.
3d ago
A Firefly Algorithm for Mixed-Variable Optimization Based on Hybrid Distance Modeling
Firefly Algorithm adaptation for optimization problems with mixed continuous, ordinal, and categorical variables.
3d ago
Towards Context-Aware Image Anonymization with Multi-Agent Reasoning
CAIAMAR framework uses multi-agent reasoning for context-aware anonymization of personally identifiable information in street-level imagery.
3d ago
HISA: Efficient Hierarchical Indexing for Fine-Grained Sparse Attention
Hierarchical indexing method HISA optimizes sparse attention mechanisms in LLMs by reducing indexer bottlenecks in token selection.
3d ago
MRI-to-CT synthesis using drifting models
Medical imaging technique using diffusion models to synthesize CT images from MRI for pelvic imaging without ionizing radiation.
3d ago
Detecting low left ventricular ejection fraction from ECG using an interpretable and scalable predictor-driven framework
Machine learning framework for detecting low left ventricular ejection fraction from ECG. Emphasizes interpretability and scalability over black-box models.
3d ago
ASTRA: Mapping Art-Technology Institutions via Conceptual Axes, Text Embeddings, and Unsupervised Clustering
ASTRA taxonomy for art-technology institutions. Uses text embeddings and clustering to map global landscape of art-tech organizations.
3d ago
OptiMer: Optimal Distribution Vector Merging Is Better than Data Mixing for Continual Pre-Training
OptiMer method for continual pre-training of LLMs. Decouples data mixture ratio selection from training by optimizing distribution vectors.
3d ago
Beta-Scheduling: Momentum from Critical Damping as a Diagnostic and Correction Tool for Neural Network Training
Beta-scheduling for neural network optimization. Derives time-varying momentum from critically damped harmonic oscillator physics.
3d ago
On the Mirage of Long-Range Dependency, with an Application to Integer Multiplication
Analysis of long-range dependency in neural networks for integer multiplication. Argues dependency is a computational artifact, not an intrinsic problem.
3d ago
Beyond Corner Patches: Semantics-Aware Backdoor Attack in Federated Learning
Backdoor attacks on federated learning with realistic semantic triggers. Proposes SABLE method using in-distribution patterns instead of synthetic corner patches.
3d ago
Security in LLM-as-a-Judge: A Comprehensive SoK
Systematization of knowledge on security and reliability risks in LLM-as-a-Judge paradigm. Documents vulnerabilities where judges become targets of adversarial manipulation.
3d ago
Task-Centric Personalized Federated Fine-Tuning of Language Models
Personalized federated learning approach for fine-tuning language models on heterogeneous tasks. Improves performance on diverse client tasks while maintaining privacy.
3d ago
RAGShield: Detecting Numerical Claim Manipulation in Government RAG Systems
Security evaluation of RAG systems in government applications. Demonstrates embedding-based defenses fail to detect subtle numerical claim manipulation in tax/benefits systems.
3d ago
Spectral Compact Training: Pre-Training Large Language Models via Permanent Truncated SVD and Stiefel QR Retraction
Spectral Compact Training (SCT) for LLMs on consumer hardware. Uses permanent truncated SVD factors to avoid materializing dense weight matrices during training.
3d ago
Screening Is Enough
Multiscreen attention mechanism for language models. Introduces absolute query-key relevance to reject irrelevant keys, addressing softmax attention limitations.
3d ago
Adaptive Stopping for Multi-Turn LLM Reasoning
Adaptive stopping mechanism for multi-turn LLM reasoning. Determines optimal stopping points for agents using retrieval-augmented generation and ReAct-style interactions.
3d ago
GPA: Learning GUI Process Automation from Demonstrations
Vision-based robotic process automation (RPA) using sequential Monte Carlo localization. Enables stable GUI automation from single demonstrations with improved robustness.
3d ago
Beyond Message Passing: A Semantic View of Agent Communication Protocols
Framework for analyzing agent communication protocols across three layers: communication, syntactic, and semantic. Systematically studies 18 representative protocols for LLM systems.
3d ago
Integrating Artificial Intelligence, Physics, and Internet of Things: A Framework for Cultural Heritage Conservation
Framework integrating IoT and AI with physics knowledge for monitoring and maintenance of cultural heritage conservation.
3d ago
Scaling DPPs for RAG: Density Meets Diversity
Method scaling determinantal point processes for RAG systems to improve diversity of retrieved context while maintaining relevance.
3d ago
DRAFT: Task Decoupled Latent Reasoning for Agent Safety
Framework for monitoring safety of tool-using LLM agents through latent reasoning that decouples safety judgment into trainable stages.
3d ago
General Explicit Network (GEN): A novel deep learning architecture for solving partial differential equations
Novel neural network architecture for solving PDEs addressing limitations of physics-informed neural networks.
3d ago
NativeTernary: A Self-Delimiting Binary Encoding with Unary Run-Length Hierarchy Markers for Ternary Neural Network Weights, Structured Data, and General Computing Infrastructure
Binary encoding scheme for ternary neural network weights enabling efficient storage and computation for compressed LLMs.
3d ago
Towards Intelligent Energy Security: A Unified Spatio-Temporal and Graph Learning Framework for Scalable Electricity Theft Detection in Smart Grids
AI framework combining spatio-temporal and graph learning for electricity theft detection in smart grids.
3d ago
Hardware-Oriented Inference Complexity of Kolmogorov-Arnold Networks
Analysis of computational efficiency for Kolmogorov-Arnold Networks on hardware-constrained deployment scenarios.
3d ago
From Model-Based Screening to Data-Driven Surrogates: A Multi-Stage Workflow for Exploring Stochastic Agent-Based Models
Multi-stage pipeline combining experimental design and machine learning surrogates to explore agent-based models efficiently.
3d ago
The limits of bio-molecular modeling with large language models : a cross-scale evaluation
Cross-scale evaluation of LLMs on biomolecular modeling tasks revealing performance gaps compared to mechanistic understanding.
3d ago
Scalable Variational Bayesian Fine-Tuning of LLMs via Orthogonalized Low-Rank Adapters
Bayesian fine-tuning method for LLMs using low-rank adapters to improve uncertainty quantification in safety-critical applications.
3d ago
Beauty in the Eye of AI: Aligning LLMs and Vision Models with Human Aesthetics in Network Visualization
Using LLMs and vision models trained on human preferences to improve network visualization aesthetics beyond traditional heuristic metrics.
3d ago
Adaptive Threshold-Driven Continuous Greedy Method for Scalable Submodular Optimization
Submodular maximization algorithm with improved approximation guarantees for combinatorial optimization problems in sensing and resource allocation.
3d ago
Adversarial Robustness of Deep State Space Models for Forecasting
Control-theoretic analysis of state-space model robustness under adversarial perturbations, examining Spacetime SSM forecasters and Kalman filter representations.
3d ago
MetaSAEs: Joint Training with a Decomposability Penalty Produces More Atomic Sparse Autoencoder Latents
MetaSAEs: sparse autoencoder training with decomposability penalty producing more atomic, single-concept latents for safety-relevant LLM applications.
3d ago
Olmo Hybrid: From Theory to Practice and Back
OLMo Hybrid: theoretical and empirical analysis of hybrid models combining linear RNNs and attention as alternatives to pure transformers with scaling benefits.
3d ago
Neural Operators for Multi-Task Control and Adaptation
Neural operator methods for multi-task optimal control problems, mapping task descriptions to control policies using permutation-invariant architectures.
3d ago
Earth Embeddings Reveal Diverse Urban Signals from Space
Benchmark of Earth embedding models (AlphaEarth, Prithvi, Clay) for neighborhood-scale urban monitoring from satellite imagery.
3d ago
Super Agents and Confounders: Influence of surrounding agents on vehicle trajectory prediction
Analysis of trajectory prediction models revealing that surrounding agents often degrade accuracy due to learned confounders, using Shapley attribution.
3d ago
Investigating Data Interventions for Subgroup Fairness: An ICU Case Study
Study of data intervention techniques for improving fairness across demographic subgroups in ICU prediction models using real healthcare data.
3d ago
Improving Feasibility via Fast Autoencoder-Based Projections
Data-driven approach using trained autoencoders as fast projectors to enforce complex nonconvex operational constraints in learning and control systems.
3d ago
Online learning of smooth functions on $\mathbb{R}$
Theoretical analysis of adversarial online learning for smooth real-valued functions on ℝ with cumulative p-loss bounds.
3d ago
Choosing the Right Regularizer for Applied ML: Simulation Benchmarks of Popular Scikit-learn Regularization Frameworks
Empirical survey comparing regularization frameworks (Ridge, Lasso, ElasticNet, Post-Lasso) across 134,400 simulations with historical development context.
3d ago
Evaluation of Bagging Predictors with Kernel Density Estimation and Bagging Score
Method for evaluating bagged neural network predictions using kernel density estimation to select representative predictions in nonlinear regression.