3/9/2026
A-3PO: Accelerating Asynchronous LLM Training with Staleness-aware Proximal Policy Approximation
A-3PO accelerates asynchronous LLM RL training with staleness-aware proximal policy approximation, improving over decoupled PPO.
3/9/2026
Understanding and Improving Hyperbolic Deep Reinforcement Learning
Analysis of optimization challenges in hyperbolic deep RL identifying gradient factors affecting training success for hierarchical state embeddings.
3/9/2026
CARE What Fails: Contrastive Anchored-REflection for Verifiable Multimodal
CARE failure-centric post-training framework uses contrastive learning on wrong rollouts to improve multimodal reasoning with verifiable rewards.
3/9/2026
LLMTM: Benchmarking and Optimizing LLMs for Temporal Motif Analysis in Dynamic Graphs
LLMTM benchmarks LLMs on temporal motif analysis in dynamic graphs for anomaly detection and structural understanding.
3/9/2026
Beyond Mapping : Domain-Invariant Representations via Spectral Embedding of Optimal Transport Plans
Spectral embedding approach for domain-invariant representations via optimal transport plans, addressing distributional shift.
3/9/2026
EDIS: Diagnosing LLM Reasoning via Entropy Dynamics
EDIS analyzes token-level entropy trajectories during LLM generation to diagnose reasoning quality beyond aggregate confidence statistics.
3/9/2026
Stress-Testing Alignment Audits With Prompt-Level Strategic Deception
Red-teaming framework to stress-test LLM alignment audits against strategic deception prompts in white-box and black-box settings.
3/9/2026
Latent Poincar\'e Shaping for Agentic Reinforcement Learning
LaPha trains AlphaZero-style LLM agents in hyperbolic space using Poincaré geometry for efficient tree search and dense reward shaping.
3/9/2026
Towards Autonomous Mathematics Research
Aletheia agent iteratively generates, verifies and revises mathematical proofs using LLMs, advancing autonomous research capabilities.
3/9/2026
FLoRG: Federated Fine-tuning with Low-rank Gram Matrices and Procrustes Alignment
FLoRG enables parameter-efficient federated fine-tuning of LLMs using low-rank adaptation with Procrustes alignment across distributed clients.
3/9/2026
Exploratory Memory-Augmented LLM Agent via Hybrid On- and Off-Policy Optimization
EMPO² framework combines on/off-policy RL with memory augmentation to improve exploration in LLM agents, addressing novel state discovery limitations.
3/9/2026
Coverage-Aware Web Crawling for Domain-Specific Supplier Discovery via a Web--Knowledge--Web Pipeline
Web-to-Knowledge-to-Web pipeline iteratively crawling domain-specific sources to discover SME suppliers in specialized industry sectors.
3/9/2026
Weight Updates as Activation Shifts: A Principled Framework for Steering
Framework establishing first-order equivalence between activation steering and weight updates for parameter-efficient LLM adaptation.
3/9/2026
MatRIS: Toward Reliable and Efficient Pretrained Machine Learning Interatomic Potentials
MatRIS: Foundation machine learning interatomic potentials with equivariant inductive bias for efficient material simulation.
3/9/2026
Rigidity-Aware Geometric Pretraining for Protein Design and Conformational Ensembles
Geometric pretraining approach for protein design combining structure learning and conformational ensembles with rigidity-aware representations.
3/9/2026
mlx-vis: GPU-Accelerated Dimensionality Reduction and Visualization on Apple Silicon
mlx-vis: Python library implementing GPU-accelerated dimensionality reduction (UMAP, t-SNE, PaCMAP, etc.) on Apple Silicon via MLX.
3/9/2026
Make VLM Recognize Visual Hallucination on Cartoon Character Image with Pose Information
Method for detecting visual hallucinations in VLM outputs on cartoon character images using pose information.
3/9/2026
BInD: Bond and Interaction-generating Diffusion Model for Multi-objective Structure-based Drug Design
BInD: Diffusion model for multi-objective structure-based drug design balancing molecular generation with protein interaction requirements.
3/9/2026
Transforming Agency. On the mode of existence of Large Language Models
Philosophical investigation of LLMs' ontological status as agents, analyzing architecture, training, and extensions enabling agent-like behavior.
3/9/2026
FALCON: Future-Aware Learning with Contextual Object-Centric Pretraining for UAV Action Recognition
FALCON: Self-supervised video pretraining for UAV action recognition addressing spatial imbalance in aerial footage with object-centric learning.
3/9/2026
An Efficient Self-supervised Seismic Data Reconstruction Method Based on Self-Consistency Learning
Self-supervised seismic data reconstruction method using self-consistency learning for handling irregularly distributed seismic receiver data.
3/9/2026
Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and Evaluation
Survey on LLMs transforming scientific research covering literature search, hypothesis generation, experimentation, content generation, and peer review assistance.
3/9/2026
RM-R1: Reward Modeling as Reasoning
Research paper proposing reward modeling with chain-of-thought reasoning for improved LLM alignment with human preferences via reinforcement learning.
3/9/2026
ContextBench: Modifying Contexts for Targeted Latent Activation
ContextBench: benchmark for generating targeted linguistically fluent inputs that activate specific latent features in language models for safety analysis.
3/9/2026
Sysformer: Safeguarding Frozen Large Language Models with Adaptive System Prompts
Sysformer: method for safeguarding frozen LLMs using adaptive system prompts to ensure safety compliance without model retraining in deployment scenarios.
3/9/2026
SPoT: Subpixel Placement of Tokens in Vision Transformers
SPoT: tokenization strategy for Vision Transformers enabling continuous subpixel token placement instead of grid-based constraints for sparse regime exploitation.
3/9/2026
Quantifying Cross-Attention Interaction in Transformers for Interpreting TCR-pMHC Binding
Cross-attention analysis in transformers for interpreting TCR-pMHC binding predictions using TULIP model for understanding immune system mechanisms.
3/9/2026
Diverse and Adaptive Behavior Curriculum for Autonomous Driving: A Student-Teacher Framework with Multi-Agent RL
Multi-agent RL framework with student-teacher curriculum for autonomous driving behavior generation addressing complex real-world traffic scenarios and critical situations.
3/9/2026
Multivariate Fields of Experts for Convergent Image Reconstruction
Multivariate fields of experts framework for learning image priors using Moreau envelopes for inverse problems including denoising, deblurring, and MRI reconstruction.
3/9/2026
Kernel VICReg for Self-Supervised Learning in Reproducing Kernel Hilbert Space
Kernel VICReg: self-supervised learning method operating in reproducing kernel Hilbert space to capture nonlinear dependencies in representation learning.
3/9/2026
VEGA: Electric Vehicle Navigation Agent via Physics-Informed Neural Operator and Proximal Policy Optimization
VEGA: AI agent for electric vehicle routing combining physics-informed neural operators with reinforcement learning for energy-aware charge-conscious path planning.
3/9/2026
Spectral/Spatial Tensor Atomic Cluster Expansion with Universal Embeddings in Cartesian Space
Tensor Atomic Cluster Expansion (TACE): equivariant atomistic machine learning in Cartesian space unifying scalar and tensorial modeling for chemistry applications.
3/9/2026
Taxonomy-aware Dynamic Motion Generation on Hyperbolic Manifolds
Taxonomy-aware dynamic motion generation for robots using hyperbolic manifolds to incorporate hierarchical biomechanical structure into movement models.
3/9/2026
Self-Speculative Masked Diffusions
Self-speculative masked diffusions: discrete data generative models reducing function evaluations through speculative sampling without factorization approximations.
3/9/2026
TCR-EML: Explainable Model Layers for TCR-pMHC Prediction
TCR-EML: explainable machine learning model layers for predicting T cell receptor-peptide MHC binding with interpretability for immunotherapy applications.
3/9/2026
How Reliable is Language Model Micro-Benchmarking?
Meta-evaluation study analyzing reliability of micro-benchmarks for ranking LLMs, comparing against full benchmarks and random sampling approaches.
3/9/2026
CanvasMAR: Improving Masked Autoregressive Video Prediction With Canvas
CanvasMAR: masked autoregressive video generation model improved with canvas mechanism to reduce frame distortion and enhance sampling quality with few steps.
3/9/2026
Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence
Study on model collapse in generative models trained iteratively on synthetic data, proposing verification methods to prevent performance degradation and reverse collapse trends.
3/9/2026
Mixed Monotonicity Reachability Analysis of Neural ODE: A Trade-Off Between Tightness and Efficiency
Interval-based reachability analysis method for Neural ODEs using mixed monotonicity techniques to verify continuous-time machine learning models of dynamical systems.
3/9/2026
Real-Time Learning of Predictive Dynamic Obstacle Models for Robotic Motion Planning
Real-time learning framework for predicting dynamic obstacle motions in robotic systems using Hankel-DMD for online nonlinear model identification from noisy measurements.
3/9/2026
FireScope: Wildfire Risk Prediction with a Chain-of-Thought Oracle
FireScope-Bench: dataset and benchmark for wildfire risk prediction using satellite imagery, climate data, and chain-of-thought reasoning with multimodal integration.
3/9/2026
SPINE: Token-Selective Test-Time Reinforcement Learning with Entropy-Band Regularization
Test-time reinforcement learning method for LLMs using token-selective entropy-band regularization to prevent response collapse.
3/9/2026
Uncertainty-Aware Subset Selection for Robust Visual Explainability under Distribution Shifts
Analyzes robustness of subset selection-based visual explanation methods under distribution shifts and out-of-distribution conditions.
3/9/2026
A Novel Patch-Based TDA Approach for Computed Tomography Imaging
Applies topological data analysis to CT imaging for improved feature extraction in medical imaging ML models.
3/9/2026
Restoring Exploration after Post-Training: Latent Exploration Decoding for Large Reasoning Models
Addresses exploration collapse in large reasoning models post-training by proposing latent exploration decoding to restore sampling diversity.
3/9/2026
Validating Interpretability in siRNA Efficacy Prediction: A Perturbation-Based, Dataset-Aware Protocol
Validates interpretability of saliency maps in siRNA efficacy prediction using perturbation-based counterfactual sensitivity testing.
3/9/2026
SWE-MiniSandbox: Container-Free Reinforcement Learning for Building Software Engineering Agents
Container-free reinforcement learning framework for training software engineering agents at scale without per-task container overhead.
3/9/2026
GaiaFlow: Semantic-Guided Diffusion Tuning for Carbon-Frugal Search
Proposes carbon-efficient neural ranking architecture for information retrieval using semantic-guided diffusion tuning.
3/9/2026
The Limits of Long-Context Reasoning in Automated Bug Fixing
Evaluates whether LLMs can reliably perform long-context code debugging and patch generation, testing limits of agentic workflows on software engineering tasks.
3/9/2026
What Topological and Geometric Structure Do Biological Foundation Models Learn? Evidence from 141 Hypotheses
Investigates geometric and topological structures learned by biological foundation models like scGPT using autonomous hypothesis screening with AI-driven workflows.