2d ago
GNN-as-Judge: Unleashing the Power of LLMs for Graph Learning with GNN Feedback
Framework combining LLMs with graph neural networks for text-attributed graph learning in low-resource settings using GNN feedback.
2d ago
Memory-Guided Trust-Region Bayesian Optimization (MG-TuRBO) for High Dimensions
Bayesian optimization method (MG-TuRBO) for high-dimensional traffic simulation calibration, comparing genetic algorithms with Bayesian approaches.
2d ago
QuanBench+: A Unified Multi-Framework Benchmark for LLM-Based Quantum Code Generation
QuanBench+ unified benchmark for LLM quantum code generation across Qiskit, PennyLane, Cirq with 42 aligned executable tasks.
2d ago
Robust Reasoning Benchmark
Benchmark evaluating robustness of LLM reasoning with 14 perturbation techniques applied to mathematical reasoning tasks.
2d ago
Silhouette Loss: Differentiable Global Structure Learning for Deep Representations
Silhouette loss function for learning discriminative representations with explicit geometric properties in embedding space.
2d ago
Distilling Genomic Models for Efficient mRNA Representation Learning via Embedding Matching
Distillation framework compressing genomic foundation models for efficient mRNA representation learning.
2d ago
MolPaQ: Modular Quantum-Classical Patch Learning for Interpretable Molecular Generation
Quantum-classical hybrid molecular generator using VAE and quantum computing for interpretable drug discovery.
2d ago
Distributionally Robust Token Optimization in RLHF
DRTO combines token-level RLHF with distributional robustness to improve LLM resilience to input perturbations and formatting changes.
2d ago
Structured Exploration and Exploitation of Label Functions for Automated Data Annotation
Automated label function generation for data annotation using LLMs with structured exploration-exploitation strategy.
2d ago
On the Spectral Geometry of Cross-Modal Representations: A Functional Map Diagnostic for Multimodal Alignment
Analysis of cross-modal alignment between vision and language encoders using functional map framework from computational geometry.
2d ago
Fully Autonomous Z-Score-Based TinyML Anomaly Detection on Resource-Constrained MCUs Using Power Side-Channel Data
TinyML Z-score anomaly detection system running on resource-constrained microcontrollers using power side-channel data.
2d ago
Multivariate Time Series Anomaly Detection via Dual-Branch Reconstruction and Autoregressive Flow-based Residual Density Estimation
Dual-branch reconstruction method for multivariate time series anomaly detection using autoregressive flow-based density estimation.
2d ago
CSAttention: Centroid-Scoring Attention for Accelerating LLM Inference
CSAttention: sparse attention mechanism for accelerating LLM inference by reducing KV-cache bottlenecks through centroid-scoring without retraining.
2d ago
FluidFlow: a flow-matching generative model for fluid dynamics surrogates on unstructured meshes
Flow-matching generative model for CFD surrogate modeling on unstructured meshes as alternative to deep learning approaches.
2d ago
Act or Escalate? Evaluating Escalation Behavior in Automation with Language Models
Framework evaluating when LLMs should act versus escalate decisions using uncertainty estimation across five real-world domains.
2d ago
EngageTriBoost: Predictive Modeling of User Engagement in Digital Mental Health Intervention Using Explainable Machine Learning
Machine learning system predicting user engagement in digital mental health interventions using explainable ML methods.
2d ago
AlphaLab: Autonomous Multi-Agent Research Across Optimization Domains with Frontier LLMs
AlphaLab autonomous research system using frontier LLMs as agents to automate full experimental cycles in optimization domains without human intervention.
2d ago
From Dispersion to Attraction: Spectral Dynamics of Hallucination Across Whisper Model Scales
Analysis of hallucination phase transitions in Whisper ASR models using spectral sensitivity theorem and eigenspectra analysis.
2d ago
Joint Interference Detection and Identification via Adversarial Multi-task Learning
Multi-task learning for wireless interference detection and identification using adversarial training methods.
2d ago
From Selection to Scheduling: Federated Geometry-Aware Correction Makes Exemplar Replay Work Better under Continual Dynamic Heterogeneity
Federated learning approach using exemplar replay to reduce catastrophic forgetting in continual learning with dynamic heterogeneity.
2d ago
StructRL: Recovering Dynamic Programming Structure from Learning Dynamics in Distributional Reinforcement Learning
StructRL: recovers dynamic programming structure from distributional RL learning dynamics. Bridges data-driven and structured approaches for stable learning.
2d ago
Practical Bayesian Inference for Speech SNNs: Uncertainty and Loss-Landscape Smoothing
Bayesian inference for spiking neural networks in speech processing. Explores weight uncertainty and loss landscape smoothing for temporal tasks.
2d ago
Evidential Transformation Network: Turning Pretrained Models into Evidential Models for Post-hoc Uncertainty Estimation
Evidential Transformation Network: adapts pretrained models for post-hoc uncertainty estimation. Efficient alternative to ensembles/MC dropout for deployed models.
2d ago
VOLTA: The Surprising Ineffectiveness of Auxiliary Losses for Calibrated Deep Learning
VOLTA: benchmark comparing uncertainty quantification methods for deep learning. Evaluates 10 UQ baselines across modalities and distribution shifts.
2d ago
Creator Incentives in Recommender Systems: A Cooperative Game-Theoretic Approach for Stable and Fair Collaboration in Multi-Agent Bandits
Game-theoretic analysis of creator incentives in multi-agent recommender systems. Cooperative game formulation for fair collaboration in bandit problems.
2d ago
PRAGMA: Revolut Foundation Model
PRAGMA: foundation models for banking event sequences. Transformer-based architecture with self-supervised pretraining on financial transaction data.
2d ago
Skip-Connected Policy Optimization for Implicit Advantage
Skip-Connected Policy Optimization (SKPO) for reinforcement learning with reasoning tasks. Improves upon GRPO by addressing high-variance advantage estimation.
2d ago
EvoLen: Evolution-Guided Tokenization for DNA Language Model
EvoLen: evolution-guided tokenization approach for DNA language models. Addresses fundamental tokenization design challenges in biological sequence modeling.
2d ago
Efficient RL Training for LLMs with Experience Replay
Experience replay for LLM post-training RL formalizing optimal buffer design as trade-off between sample efficiency and data freshness.
2d ago
Every Response Counts: Quantifying Uncertainty of LLM-based Multi-Agent Systems through Tensor Decomposition
Tensor decomposition method quantifying uncertainty in LLM-based multi-agent systems accounting for communication and role dependencies.
2d ago
Wireless Communication Enhanced Value Decomposition for Multi-Agent Reinforcement Learning
CLOVER framework for multi-agent RL cooperation conditioning value decomposition on realistic wireless communication graphs.
2d ago
A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need
LottaLoRA training paradigm showing frozen random backbones with trained LoRA adapters recover 96-100% performance across diverse tasks.
2d ago
Adversarial Sensor Errors for Safe and Robust Wind Turbine Fleet Control
Adversarial sensor error framework for robust wind turbine fleet control against measurement errors and hacking.
2d ago
Adaptive Simulation Experiment for LLM Policy Optimization
Adaptive simulation experiment framework using pairwise comparisons to optimize LLM policies for operations management tasks.
2d ago
$p1$: Better Prompt Optimization with Fewer Prompts
Prompt optimization method decomposing reward variance into response and prompt variance to identify task amenability to optimization.
2d ago
Alleviating Community Fear in Disasters via Multi-Agent Actor-Critic Reinforcement Learning
Multi-agent actor-critic reinforcement learning for disaster resilience controlling power, communication, and emergency response systems.
2d ago
Structural Evaluation Metrics for SVG Generation via Leave-One-Out Analysis
Evaluation metrics for SVG generation via element-level structural analysis using leave-one-out evaluation.
2d ago
HiFloat4 Format for Language Model Pre-training on Ascend NPUs
4-bit floating-point format (HiFloat4) for efficient language model pre-training on Ascend NPU hardware.
2d ago
Post-Hoc Guidance for Consistency Models by Joint Flow Distribution Learning
Guidance method for consistency models using joint flow distribution learning to enable classifier-free guidance without separate teacher model.
2d ago
Discrete Meanflow Training Curriculum
Training curriculum method for discrete flow-based image generation models to improve one-step sampling stability and quality.
2d ago
Spectral Geometry of LoRA Adapters Encodes Training Objective and Predicts Harmful Compliance
Analysis of LoRA adapter spectral geometry to identify fine-tuning objectives and predict harmful model behavior in language models.
2d ago
Dictionary-Aligned Concept Control for Safeguarding Multimodal LLMs
Safety steering mechanism for multimodal LLMs using dictionary-aligned concept control to prevent unsafe outputs without retraining.
2d ago
Finite-Sample Analysis of Nonlinear Independent Component Analysis:Sample Complexity and Identifiability Bounds
Theoretical analysis of finite-sample properties and identifiability bounds for nonlinear Independent Component Analysis algorithms.
2d ago
Temporal Dropout Risk in Learning Analytics: A Harmonized Survival Benchmark Across Dynamic and Early-Window Representations
Survival analysis benchmark for predicting student dropout in learning analytics using OULAD dataset with dynamic and static representations.
2d ago
How does Chain of Thought decompose complex tasks?
Demonstrates power-law scaling of classification error with number of classes and how chain-of-thought decomposition reduces error through task splitting.
2d ago
A Mathematical Framework for Temporal Modeling and Counterfactual Policy Simulation of Student Dropout
Temporal modeling framework for predicting student dropout using LMS data and logistic regression with counterfactual policy simulation.
2d ago
Revisiting the Capacity Gap in Chain-of-Thought Distillation from a Practical Perspective
Practical analysis of chain-of-thought distillation from students to teachers, revisiting capacity gap assumptions and baseline comparisons.
2d ago
Uncertainty-Aware Transformers: Conformal Prediction for Language Models
Conformal prediction framework for transformers providing uncertainty quantification and calibration for trustworthy LLM deployment.
2d ago
A Closer Look at the Application of Causal Inference in Graph Representation Learning
Analysis of causal inference applications in graph representation learning and risks of aggregating graph elements.
2d ago
Adaptive Candidate Point Thompson Sampling for High-Dimensional Bayesian Optimization
Adaptive Thompson sampling for high-dimensional Bayesian optimization addressing sparse candidate point grids.