3/19/2026
Genomic Next-Token Predictors are In-Context Learners
Demonstrates in-context learning emerges organically in genomic sequence models trained with next-token prediction on DNA sequences.
3/19/2026
Provably Safe Model Updates
Develops methods for provably safe ML model updates preventing catastrophic forgetting and alignment drift in dynamic environments.
3/19/2026
Efficient Cross-Domain Offline Reinforcement Learning with Dynamics- and Value-Aligned Data Filtering
Proposes data filtering method for cross-domain offline RL addressing dynamics misalignment between source and target domains.
3/19/2026
A Comedy of Estimators: On KL Regularization in RL Training of LLMs
Analyzes KL regularization estimators in RL training of LLMs, comparing bias-variance tradeoffs of different approximation methods.
3/19/2026
VL-RouterBench: A Benchmark for Vision-Language Model Routing
VL-RouterBench benchmark for evaluating vision-language model routing systems with quality-cost tradeoff assessment at scale.
3/19/2026
Evaluating Feature Dependent Noise in Preference-based Reinforcement Learning
Evaluates feature-dependent noise in preference-based reinforcement learning with realistic noise patterns correlated to observations.
3/19/2026
GIFT: Reconciling Post-Training Objectives via Finite-Temperature Gibbs Initialization
Proposes GIFT method reconciling SFT and RL post-training for Large Reasoning Models via Gibbs initialization to prevent distributional collapse.
3/19/2026
Global Optimization By Gradient From Hierarchical Score-Matching Spaces
Solves constrained optimization problems via gradient-based methods using hierarchical score-matching spaces to overcome local optima.
3/19/2026
Learning Adaptive Distribution Alignment with Neural Characteristic Function for Graph Domain Adaptation
Proposes neural characteristic function approach for graph domain adaptation addressing distributional shifts without manual feature design.
3/19/2026
Distribution-Free Sequential Prediction with Abstentions
Studies sequential prediction with option to abstain in semi-adversarial settings mixing adversarial and stochastic instances.
3/19/2026
A Deep Surrogate Model for Robust and Generalizable Long-Term Blast Wave Prediction
Creates deep surrogate model for blast wave prediction that generalizes to out-of-distribution urban scenarios using machine learning.
3/19/2026
Federated Causal Representation Learning in State-Space Systems for Decentralized Counterfactual Reasoning
Develops federated causal representation learning for decentralized counterfactual reasoning across coupled industrial systems while preserving data privacy.
3/19/2026
Detecting Transportation Mode Using Dense Smartphone GPS Trajectories and Transformer Models
Introduces SpeedTransformer, a transformer-based model for detecting transportation modes from smartphone GPS speed data.
3/19/2026
Hyperparameter Trajectory Inference with Conditional Lagrangian Optimal Transport
Proposes Hyperparameter Trajectory Inference to adjust neural network hyperparameters post-deployment without full retraining using optimal transport.
3/19/2026
Pretrained Vision-Language-Action Models are Surprisingly Resistant to Forgetting in Continual Learning
Studies how pretrained Vision-Language-Action models resist catastrophic forgetting during continual learning in robot policy training.
3/19/2026
Thin Keys, Full Values: Reducing KV Cache via Low-Dimensional Attention Selection
Reduces transformer KV cache by using low-dimensional keys for attention selection while maintaining high-dimensional values, achieving O(log N) dimensional compression.
3/19/2026
JAWS: Enhancing Long-term Rollout of Neural PDE Solvers via Spatially-Adaptive Jacobian Regularization
JAWS improves neural PDE solvers' long-term rollouts using spatially-adaptive Jacobian regularization to prevent spectral blow-up and unphysical divergence.
3/19/2026
Exploiting Adaptive Channel Pruning for Communication-Efficient Split Learning
Adaptive channel pruning technique reduces communication overhead in split learning by selectively transmitting intermediate feature representations.
3/19/2026
Meta-Reinforcement Learning with Self-Reflection for Agentic Search
MR-Search proposes meta-reinforcement learning with self-reflection for agentic search, enabling agents to adapt strategies across episodes and improve in-context exploration.
3/19/2026
Disentangled Representation Learning through Unsupervised Symmetry Group Discovery
Method for embodied agents to autonomously discover symmetry group structure for disentangled representation learning without requiring prior knowledge of group properties.
3/19/2026
Deep learning and the rate of approximation by flows
Theoretical investigation of deep residual networks' approximation capacity in continuous dynamical systems, quantifying minimal time-horizons for diffeomorphism approximation.
3/19/2026
OMNIFLOW: A Physics-Grounded Multimodal Agent for Generalized Scientific Reasoning
OMNIFLOW is a multimodal agent combining LLMs with physics-grounded reasoning for scientific tasks involving PDEs, addressing hallucinations through cross-domain generalization.
3/19/2026
PhasorFlow: A Python Library for Unit Circle Based Computing
PhasorFlow: open-source Python library for computing on unit circle using complex phasors and unitary wave interference gates.
3/19/2026
Trajectory-Optimized Time Reparameterization for Learning-Compatible Reduced-Order Modeling of Stiff Dynamical Systems
Time reparameterization technique for machine-learning reduced-order models of stiff dynamical systems improving training efficiency.
3/19/2026
The Moral Foundations Reddit Corpus
Reddit corpus annotated with moral sentiment and framing for NLP tasks related to moral language detection and analysis.
3/19/2026
QFT: Quantized Full-parameter Tuning of LLMs with Affordable Resources
QFT: quantization-based approach for full-parameter fine-tuning of large language models with limited computational resources.
3/19/2026
Reinforcement learning with learned gadgets to tackle hard quantum problems on real hardware
Reinforcement learning method for quantum circuit design handling device noise and connectivity constraints on real quantum hardware.
3/19/2026
Byte-token Enhanced Language Models for Temporal Point Processes Analysis
Byte-token enhanced language models for temporal point processes analysis to model event sequences with temporal dynamics and textual descriptions.
3/19/2026
Integrating Arithmetic Learning Improves Mathematical Reasoning in Smaller Models
Method for improving mathematical reasoning in smaller LLMs by integrating arithmetic learning with knowledge distillation and data augmentation.
3/19/2026
Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Survey
Survey of edge-cloud collaborative computing paradigms for distributed AI deployment, covering model optimization and LLM inference strategies.
3/19/2026
Optimization over Trained (and Sparse) Neural Networks: A Surrogate within a Surrogate
Framework for constraint learning using pruned neural networks as tractable surrogates in optimization problems.
3/19/2026
Optimizing Binary and Ternary Neural Network Inference on RRAM Crossbars using CIM-Explorer
CIM-Explorer tool for optimizing binary and ternary neural networks on RRAM crossbar hardware architectures.
3/19/2026
A quantitative analysis of semantic information in deep representations of text and images
Information Imbalance metric for analyzing semantic information alignment in deep representations across text and image models.
3/19/2026
Statistical Inference for Online Algorithms
Methods for constructing confidence intervals and hypothesis tests for functionals derived from online/sequential algorithms with computational constraints.
3/19/2026
BiomedSQL: Text-to-SQL for Scientific Reasoning on Biomedical Knowledge Bases
BiomedSQL benchmark for evaluating text-to-SQL systems on biomedical knowledge bases requiring implicit domain reasoning and scientific understanding.
3/19/2026
Code Roulette: How Prompt Variability Affects LLM Code Generation
Study on how prompt variability affects LLM code generation quality and functionality across different user backgrounds and expertise levels.
3/19/2026
Decadal sink-source shifts of forest aboveground carbon since 1988
Deep learning models integrated with satellite data to reconstruct global forest carbon dynamics from 1988-2021 with uncertainty quantification.
3/19/2026
Hebbian Physics Networks: A Self-Organizing Computational Architecture Based on Local Physical Laws
Hebbian Physics Networks: self-organizing computational architecture using plastic transport geometry for solving physical dynamics problems.
3/19/2026
From Street Form to Spatial Justice: Explaining Urban Exercise Inequality via a Triadic SHAP-Informed Framework
SHAP-based framework for analyzing urban exercise inequality using spatial theory and machine learning on Shenzhen street data.
3/19/2026
Robust estimation of heterogeneous treatment effects in randomized trials leveraging external data
QR-learner model for estimating conditional treatment effects in trials using external data.
3/19/2026
ToolRegistry: A Protocol-Agnostic Tool Management Library for Function-Calling LLMs
ToolRegistry: protocol-agnostic tool management library for function-calling LLMs, addressing fragmentation in tool integration.
3/19/2026
Exact Generalisation Error Exposes Benchmarks Skew Graph Neural Networks Success (or Failure)
Analysis of GNN generalization error to explain performance variance and benchmark skew in graph neural networks.
3/19/2026
InPhyRe Discovers: Large Multimodal Models Struggle in Inductive Physical Reasoning
Benchmark study showing large multimodal models fail at inductive physical reasoning beyond training distribution.
3/19/2026
EdiVal-Agent: An Object-Centric Framework for Automated, Fine-Grained Evaluation of Multi-Turn Editing
EdiVal-Agent framework for automated, fine-grained evaluation of multi-turn image editing using object-centric assessment.
3/19/2026
Detecting Data Contamination from Reinforcement Learning Post-training for Large Language Models
Detection methods for data contamination in RL post-training phase of LLMs, addressing evaluation validity gap.
3/19/2026
On the identifiability of causal graphs with multiple environments
Causal discovery method using multi-environment data to achieve full causal graph identifiability with minimal environments.
3/19/2026
CBF-RL: Safety Filtering Reinforcement Learning in Training with Control Barrier Functions
CBF-RL integrates Control Barrier Functions into RL training to enforce safety constraints during policy learning.
3/19/2026
Learning Time-Varying Graphs from Incomplete Graph Signals
Unified optimization framework for jointly inferring time-varying network topologies and imputing missing graph signal data.
3/19/2026
Neighbor GRPO: Contrastive ODE Policy Optimization Aligns Flow Models
Neighbor GRPO extends Group Relative Policy Optimization to flow matching models with contrastive ODE-based approach for generative model alignment.
3/19/2026
Representation-Aware Unlearning via Activation Signatures: From Suppression to Knowledge-Signature Erasure
Knowledge Immunization Framework for selective knowledge erasure from LLMs via representation-aware activation signatures, addressing GDPR and safety.