3/10/2026
UniWhisper: Efficient Continual Multi-task Training for Robust Universal Audio Representation
Continual multi-task training framework for universal audio representation across speech, environmental sounds, and music.
3/10/2026
CryoNet.Refine: A One-step Diffusion Model for Rapid Refinement of Structural Models with Cryo-EM Density Map Restraints
Deep learning framework for automated refinement of protein structures using cryo-EM density maps with diffusion models.
3/10/2026
Autoregressive Visual Decoding from EEG Signals
Autoregressive decoding model for reconstructing visual information from EEG brain signals using diffusion-based approach.
3/10/2026
CeRA: Breaking the Linear Ceiling of Low-Rank Adaptation via Manifold Expansion
CeRA improves low-rank adaptation for LLM fine-tuning by adding manifold expansion via gating and dropout, addressing linear limitations.
3/10/2026
Scaling Search Relevance: Augmenting App Store Ranking with LLM-Generated Judgments
Combines behavioral and textual relevance signals using LLMs to improve app store search ranking at scale.
3/10/2026
Attn-QAT: 4-Bit Attention With Quantization-Aware Training
First systematic 4-bit quantization-aware training study for attention mechanisms enabling end-to-end FP4 computation on emerging GPUs.
3/10/2026
PEPA: a Persistently Autonomous Embodied Agent with Personalities
PEPA: embodied AI agent framework with personality-driven persistent autonomy enabling self-sustaining goals without external task specification.
3/10/2026
Conformal Prediction for Risk-Controlled Medical Entity Extraction Across Clinical Domains
Conformal prediction framework providing finite-sample coverage guarantees for LLM-based medical entity extraction across clinical domains.
3/10/2026
A Detection-Gated Pipeline for Robust Glottal Area Waveform Extraction and Clinical Pathology Assessment
Deep learning pipeline for glottal area segmentation in laryngeal videoendoscopy with detection gating for clinical pathology assessment.
3/10/2026
Slurry-as-a-Service: A Modest Proposal on Scalable Pluralistic Alignment for Nutrient Optimization
Satirical paper presenting pluralistic alignment for LLMs in implausible mulching context; appears to be parody without technical substance.
3/10/2026
Human-Certified Module Repositories for the AI Age
Architectural model for trustworthy AI-assisted software via human-certified module repositories ensuring reliability of AI-assembled systems.
3/10/2026
iGVLM: Dynamic Instruction-Guided Vision Encoding for Question-Aware Multimodal Understanding
iGVLM: framework enabling dynamic instruction-guided vision encoding in LVLMs for task-specific visual understanding.
3/10/2026
ITO: Images and Texts as One via Synergizing Multiple Alignment and Training-Time Fusion
ITO: framework for image-text contrastive learning using multiple alignment and training-time fusion to reduce modality bias.
3/10/2026
Interpretable Motion-Attentive Maps: Spatio-Temporally Localizing Concepts in Video Diffusion Transformers
Interpretability method using attention maps to localize motion concepts in video diffusion transformers.
3/10/2026
Why Adam Can Beat SGD: Second-Moment Normalization Yields Sharper Tails
Theoretical analysis proving Adam optimizer outperforms SGD through second-moment normalization creating sharper gradient tails.
3/10/2026
Information Routing in Atomistic Foundation Models: How Task Alignment and Equivariance Shape Linear Disentanglement
Compositional Probe Decomposition method analyzing how molecular foundation models separate geometric and compositional information.
3/10/2026
Non-Invasive Reconstruction of Intracranial EEG Across the Deep Temporal Lobe from Scalp EEG based on Conditional Normalizing Flow
Conditional normalizing flow method for reconstructing deep brain EEG signals from scalp measurements.
3/10/2026
Test-Time Meta-Adaptation with Self-Synthesis
MASS: meta-learning framework enabling LLMs to self-adapt at test time by generating synthetic training data for improved downstream performance.
3/10/2026
ZipMap: Linear-Time Stateful 3D Reconstruction via Test-Time Training
ZipMap: feed-forward transformer model achieving linear-time 3D reconstruction from multiple images via stateful processing.
3/10/2026
How Professional Visual Artists are Negotiating Generative AI in the Workplace
Survey of 378 professional visual artists on workplace impacts of generative AI adoption and career concerns.
3/10/2026
Neuro-Symbolic Financial Reasoning via Deterministic Fact Ledgers and Adversarial Low-Latency Hallucination Detector
Neuro-symbolic approach combining LLMs with deterministic fact ledgers and hallucination detection for financial reasoning without arithmetic errors.
3/10/2026
GALACTIC: Global and Local Agnostic Counterfactuals for Time-series Clustering
Explainability method using counterfactual explanations to understand time-series clustering transitions.
3/10/2026
SAIL: Similarity-Aware Guidance and Inter-Caption Augmentation-based Learning for Weakly-Supervised Dense Video Captioning
Weakly-supervised method for localizing and describing video events using Gaussian masking and caption augmentation techniques.
3/10/2026
Bridging Domains through Subspace-Aware Model Merging
Research on merging task-specific models into consolidated ones, analyzing parameter competition and domain generalization effects.
3/10/2026
vLLM Hook v0: A Plug-in for Programming Model Internals on vLLM
vLLM Hook v0 plugin enabling programmable access to LLM model internals for test-time alignment and inference optimization in vLLM serving engine.
3/10/2026
How Attention Sinks Emerge in Large Language Models: An Interpretability Perspective
Interpretability study on attention sinks in LLMs, explaining why models allocate disproportionate attention to specific tokens including first token bias.
3/10/2026
FuzzingRL: Reinforcement Fuzz-Testing for Revealing VLM Failures
FuzzingRL approach using reinforcement learning for fuzz testing Vision Language Models to automatically generate failure-inducing queries.
3/10/2026
Switchable Activation Networks
Switchable Activation Networks that dynamically select activation functions for computational efficiency in LLMs and vision-action models during inference.
3/10/2026
Khatri-Rao Clustering for Data Summarization
Khatri-Rao Clustering approach for data summarization using centroid-based clustering with reduced redundancy in prototypes.
3/10/2026
Know When You're Wrong: Aligning Confidence with Correctness for LLM Error Detection
Method to align LLM confidence scores with correctness using output token probabilities for reliable error detection and hallucination identification.
3/10/2026
Structure-Aware Set Transformers: Temporal and Variable-Type Attention Biases for Asynchronous Clinical Time Series
Set Transformers with temporal and variable-type attention biases for asynchronous clinical time series in EHR data without imputation.
3/10/2026
LegoNet: Memory Footprint Reduction Through Block Weight Clustering
LegoNet compression technique for neural networks using block weight clustering to reduce memory footprint for embedded device deployment.
3/10/2026
Valid Feature-Level Inference for Tabular Foundation Models via the Conditional Randomization Test
Conditional Randomization Test approach for valid feature-level hypothesis testing and p-values in tabular foundation models.
3/10/2026
CapTrack: Multifaceted Evaluation of Forgetting in LLM Post-Training
CapTrack benchmark for evaluating multi-faceted forgetting in LLM post-training beyond parametric knowledge loss, addressing domain adaptation challenges.
3/10/2026
Consensus is Not Verification: Why Crowd Wisdom Strategies Fail for LLM Truthfulness
Research showing majority-voting and ensemble inference methods fail to improve LLM truthfulness without external verification, unlike in math/code domains.
3/10/2026
OptiRoulette Optimizer: A New Stochastic Meta-Optimizer for up to 5.3x Faster Convergence
OptiRoulette meta-optimizer that dynamically selects update rules during training via warmup locking and random sampling. Torch-compatible drop-in component achieving 5.3x faster convergence.
3/10/2026
Correlation Analysis of Generative Models
Theoretical analysis of diffusion models and flow matching using unified representation via linear equations. Discusses correlation between noisy data and predictions.
3/10/2026
Annealed Co-Generation: Disentangling Variables via Progressive Pairwise Modeling
Annealed Co-Generation framework for multivariate scientific data generation using progressive pairwise diffusion modeling instead of joint high-dimensional modeling.
3/10/2026
RACER: Risk-Aware Calibrated Efficient Routing for Large Language Models
RACER system for efficient multi-model LLM routing formulated as risk-aware optimization problem. Extends base routers to minimize cost-performance trade-off.
3/10/2026
Evo: Autoregressive-Diffusion Large Language Models with Evolving Balance
Novel language model combining autoregressive and diffusion-based generation through latent trajectory modeling with evolving balance parameter.
3/10/2026
Distilling and Adapting: A Topology-Aware Framework for Zero-Shot Interaction Prediction in Multiplex Biological Networks
Framework for zero-shot prediction in multiplex biological networks using topology-aware distillation and adaptation methods.
3/10/2026
Not all tokens are needed(NAT): token efficient reinforcement learning
Framework for token-efficient reinforcement learning in LLMs. Proposes NAT to reduce computational cost of backpropagation over long chain-of-thought trajectories during training.
3/10/2026
Reward Under Attack: Analyzing the Robustness and Hackability of Process Reward Models
Research on vulnerabilities in Process Reward Models used in LLM reasoning pipelines. Introduces diagnostic framework to quantify adversarial exploitability and fluency-logic dissociation.
3/10/2026
From ARIMA to Attention: Power Load Forecasting Using Temporal Deep Learning
Empirical comparison of ARIMA, LSTM, BiLSTM, and Transformer for short-term power load forecasting.
3/10/2026
Advances in GRPO for Generation Models: A Survey
Survey of Group Relative Policy Optimization for aligning generative models with human preferences.
3/10/2026
Pavement Missing Condition Data Imputation through Collective Learning-Based Graph Neural Networks
Graph neural networks for imputing missing pavement condition data in road networks.
3/10/2026
Grouter: Decoupling Routing from Representation for Accelerated MoE Training
Grouter: decoupled routing method for accelerating Mixture-of-Experts training with structural priors.
3/10/2026
Leakage Safe Graph Features for Interpretable Fraud Detection in Temporal Transaction Networks
Leakage-safe graph feature extraction for fraud detection in temporal transaction networks.
3/10/2026
A new Uncertainty Principle in Machine Learning
Theoretical analysis of polynomial approximation and Heaviside/sigmoid expansions in neural networks.
3/10/2026
Graph Property Inference in Small Language Models: Effects of Representation and Inference Strategy
Graph property inference in small language models: effects of representation on structured reasoning.