research

On the Cost and Benefit of Chain of Thought: A Learning-Theoretic Perspective

arXiv:2605.21260v1 Announce Type: new Abstract: We develop a learning-theoretic framework for understanding Chain of Thought (CoT). We model CoT as the interaction between an answer map and a chain ru

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One Operator to Rule Them All? On Boundary-Indexed Operator Families in Neural PDE Solvers

DGX agent

arXiv:2603.01406v2 Announce Type: replace Abstract: Neural PDE solvers are often described as learning solution operators that map problem data to PDE solutions. In this work, we argue that this inter

researcharxiv-cs-lg

21 May 2026

OpenSeisML: Open Large-Scale Real Seismic and well-log Dataset for Generative AI

arXiv:2605.20539v1 Announce Type: new Abstract: The advent of machine learning (ML) and computer vision has significantly accelerated seismic inversion workflows by reducing the computational cost of

Optimal Query Allocation in Extractive QA with LLMs: A Learning-to-Defer Framework with Theoretical Guarantees

arXiv:2410.15761v4 Announce Type: replace Abstract: Large Language Models excel in generative tasks but exhibit inefficiencies in structured text selection, particularly in extractive question answeri

Oracle Supervision Transfers for Hyperparameter Prediction in Model-Based Image Denoising

arXiv:2605.20479v1 Announce Type: new Abstract: Hyperparameter prediction is a critical practical bottleneck for model-based image denoisers, ranging from classical TV/TGV variational solvers to moder

Ordering Matters: Rank-Aware Selective Fusion for Blended Emotion Recognition

arXiv:2605.21417v1 Announce Type: new Abstract: Blended emotion recognition is challenging because emotions are often expressed as mixtures of subtle and overlapping multimodal cues rather than a sing

PerpetualWonder: Long-Horizon Action-Conditioned 4D Scene Generation

arXiv:2602.04876v2 Announce Type: replace Abstract: We introduce PerpetualWonder, a hybrid generative simulator that enables long-horizon, action-conditioned 4D scene generation from a single image. C

Physics-informed convolutional neural networks for fluid flow through porous media

arXiv:2605.20250v1 Announce Type: new Abstract: Accurate simulation of fluid flow in porous media is challenging due to complex pore-space geometries and the computational cost of solving the Navier-S

Pixel Wised Lesion Prediction on COVID-19 CT Imagery: A Comparative Analysis of Automated Image Segmentation Architectures

arXiv:2605.20459v1 Announce Type: new Abstract: In recent years, there has been a notable increase in the level of attention that is given to algorithms based on deep learning in the context of medica

Platonic Representations in the Human Brain: Unsupervised Recovery of Universal Geometry

arXiv:2605.20496v1 Announce Type: cross Abstract: The Strong Platonic Representation Hypothesis suggests that representational convergence in artificial neural networks can be harnessed constructively

Playing Devil's Advocate: Off-the-Shelf Persona Vectors Rival Targeted Steering for Sycophancy

arXiv:2605.21006v1 Announce Type: cross Abstract: We study the effect of different persona on extbf{sycophancy}: model's agreement with users even when the user is incorrect. The standard mitigation,

Plug-and-Play Spiking Operators: Breaking the Nonlinearity Bottleneck in Spiking Transformers

arXiv:2605.20289v1 Announce Type: new Abstract: ANN-to-SNN conversion offers a practical, training-free route to spiking large language models. However, current pipelines primarily focus on spike-driv

Polynomial-Time Robust Multiclass Linear Classification under Gaussian Marginals

arXiv:2605.21428v1 Announce Type: new Abstract: We study the task of agnostic learning of multiclass linear classifiers under the Gaussian distribution. Given labeled examples (x, y) from a distributi

Praxium: Diagnosing Cloud Anomalies with AI-based Telemetry and Dependency Analysis

arXiv:2603.23890v2 Announce Type: replace-cross Abstract: As the modern microservice architecture for cloud applications grows in popularity, cloud services are becoming increasingly complex and more

PREF: Phasorial Embedding Fields for Compact Neural Representations

arXiv:2205.13524v4 Announce Type: replace Abstract: We present an efficient frequency-based neural representation termed PREF: a shallow MLP augmented with a phasor volume that covers significant bord

PrefixWall: Mitigating Prefix Caching Side Channels in Shared LLM Systems

arXiv:2603.10726v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) rely on optimizations like Automatic Prefix Caching (APC) to accelerate inference. APC works by reusing previousl

Prism: Structural Symmetry Scanning via Duality-Constrained Laplacian Projection

arXiv:2605.20245v1 Announce Type: cross Abstract: We introduce extbf{Prism}, a framework for structural symmetry diagnosis in complex networks. Given a graph Laplacian L and a duality operator P (a sy

Prompt Reinjection: Alleviating Prompt Forgetting in Multimodal Diffusion Transformers

arXiv:2602.06886v3 Announce Type: replace Abstract: Multimodal Diffusion Transformers (MMDiTs) for text-to-image generation maintain separate text and image branches, with bidirectional information fl

ProtoPathway: Biologically Structured Prototype-Pathway Fusion for Multimodal Cancer Survival Prediction

arXiv:2605.21454v1 Announce Type: new Abstract: We introduce ProtoPathway, an interpretable-by-design multimodal framework for cancer survival prediction that unifies whole slide imaging and transcrip

Provably Learning Diffusion Models under the Manifold Hypothesis: Collapse and Refine

arXiv:2605.20235v1 Announce Type: new Abstract: Diffusion models generate high-dimensional data with remarkable quality, yet how their training efficiently learns the score function, bypassing the cur

Q-ARVD: Quantizing Autoregressive Video Diffusion Models

arXiv:2605.21072v1 Announce Type: new Abstract: Autoregressive video diffusion models (ARVDs) have emerged as a promising architecture for streaming video generation, paving the way for real-time inte

Q-SYNTH: Hybrid Quantum-Classical Adversarial Augmentation for Imbalanced Fraud Detection

arXiv:2605.21164v1 Announce Type: new Abstract: Credit card fraud detection is fundamentally challenged by extreme class imbalance, where fraudulent transactions are rare yet operationally critical. T

Quantifying the cross-linguistic effects of syncretism on agreement attraction

arXiv:2605.21403v1 Announce Type: new Abstract: Agreement attraction errors, in which a verb erroneously agrees with an intervening noun rather than its grammatical head, are amplified by morphologica

Reasoning-Trace Collapse: Evaluating the Loss of Explicit Reasoning During Fine-Tuning

arXiv:2605.21127v1 Announce Type: new Abstract: Explicit reasoning models are trained to produce intermediate reasoning traces before final answers, but downstream fine-tuning is often performed on or

Reinforcement Learning-based Control via Y-wise Affine Neural Networks: Comparative Case Studies for Chemical Processes

arXiv:2605.21211v1 Announce Type: cross Abstract: In this work we present an efficient and practically implementable approach for the application of reinforcement learning (RL)-based control in chemic

Reliable Automated Triage in Spanish Clinical Notes: A Hybrid Framework for Risk-Aware HIV Suspicion Identification

arXiv:2605.21256v1 Announce Type: new Abstract: Standard clinical Natural Language Processing (NLP) benchmarks often yield inflated metrics by forcing deterministic classification on ambiguous instanc

RelWitness: Open-Vocabulary 3D Scene Graph Generation with Visual-Geometric Relation Witnesses

arXiv:2605.20823v1 Announce Type: new Abstract: Open-vocabulary 3D scene graph generation seeks to describe object instances and their relations with flexible natural-language predicates. The central

ReMATF: Recurrent Motion-Adaptive Multi-scale Turbulence Mitigation for Dynamic Scenes

arXiv:2605.21440v1 Announce Type: new Abstract: Atmospheric turbulence severely degrades video quality by introducing distortions such as geometric warping, blur, and temporal flickering, posing signi

ResNet-50 with Class Reweighting and Anatomy-Guided Temporal Decoding for Gastrointestinal Video Analysis

arXiv:2603.17784v2 Announce Type: replace Abstract: We developed a multi-label gastrointestinal video analysis pipeline based on a ResNet-50 frame classifier followed by anatomy-guided temporal event

Retrospective Sparse Attention for Efficient Long-Context Generation

arXiv:2508.09001v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly deployed in long-context tasks such as reasoning, code generation, and multi-turn dialogue. However, i

ReversedQ: Opportunities for Faster Q-Learning in Episodic Online Reinforcement Learning

arXiv:2605.20592v1 Announce Type: new Abstract: We study model-free Q-learning in finite-horizon episodic Markov Decision Processes (MDPs) with stationary dynamics across episodes. We identify a centr

Reviving Error Correction in Modern Deep Time-Series Forecasting

arXiv:2605.21088v1 Announce Type: new Abstract: Modern deep-learning models have achieved remarkable success in time-series forecasting. Yet, their performance degrades in long-term prediction due to

Riemannian MeanFlow for One-Step Generation on Manifolds

arXiv:2603.10718v2 Announce Type: replace Abstract: Flow Matching enables simulation-free training of generative models on Riemannian manifolds, yet sampling typically still relies on numerically inte

RISE: Reliable Improvement in Self-Evolving Vision-Language Models

arXiv:2605.20914v1 Announce Type: new Abstract: Vision-language models (VLMs) have achieved strong multimodal reasoning capabilities, but further improving them still relies heavily on large-scale hum

RoadTones: Tone Controllable Text Generation from Road Event Videos

arXiv:2605.21411v1 Announce Type: new Abstract: Existing video-language models can generate factual descriptions of road events but lack control over how these events are expressed: their tone, urgenc

ROAR-3D: Routing Arbitrary Views for High-Fidelity 3D Generation

arXiv:2605.21121v1 Announce Type: new Abstract: Single-image-to-3D generative models can now produce high-quality geometry, yet conditioning on a single view inevitably introduces ambiguity about unse

Robust Subspace-Constrained Quadratic Models for Low-Dimensional Structure Learning

arXiv:2605.20300v1 Announce Type: new Abstract: In this paper, we propose a robust subspace-constrained quadratic model (SCQM) for learning low-dimensional structure from high-dimensional data. Buildi

RoPeSLR: 3D RoPE-driven Sparse-LowRank Attention for Efficient Diffusion Transformers

arXiv:2605.20659v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) have revolutionized high-fidelity video generation, yet their O(L^2) attention complexity poses a formidable bottleneck fo

Same Target, Different Basins: Hard vs. Soft Labels for Annotator Distributions

arXiv:2605.20642v1 Announce Type: new Abstract: When annotators disagree, that disagreement can reflect epistemic uncertainty rather than simple label noise. We study hard-label delivery as an alterna

Sample Complexity of Transfer Learning: An Optimal Transport Approach

arXiv:2605.20545v1 Announce Type: cross Abstract: Transfer learning is an essential technique for many machine learning/AI models of complex structures such as large language models and generative AI.

SAVER: Selective As-Needed Vision Evidence for Multimodal Information Extraction

arXiv:2605.20713v1 Announce Type: new Abstract: Multimodal IE in social media is difficult because a post may attach multiple images that are weakly related, redundant, or even misleading with respect

Scalable Multi-robot Motion Planning via Hierarchical Subproblem Expansion and Workspace Decomposition Refinement

arXiv:2605.20395v1 Announce Type: new Abstract: A fundamental challenge in multi-robot motion planning is achieving sufficient coordination to avoid inter-robot conflicts without incurring the large c

researcharxiv-cs-ro

Scaling creativity in the age of AI

Storytelling is core to humanity’s DNA, stemming from our impulse to express ideals, warnings, hopes, and experiences. Technology has always been woven through the medium and the distribution: from ea

researchmit-tech-review

Score-Based Causal Discovery of Latent Variable Causal Models

arXiv:2605.20396v1 Announce Type: new Abstract: Identifying latent variables and the causal structure involving them is essential across various scientific fields. While many existing works fall under

SDM: A Powerful Tool for Evaluating Model Robustness

arXiv:2605.20308v1 Announce Type: new Abstract: Gradient-based attacks are important methods for evaluating model robustness. However, since the proposal of APGD, it has been difficult for such method

Self-Improving Skill Learning for Robust Skill-based Meta-Reinforcement Learning

arXiv:2502.03752v5 Announce Type: replace Abstract: Meta-reinforcement learning (Meta-RL) facilitates rapid adaptation to unseen tasks but faces challenges in long-horizon environments. Skill-based ap

Self-Training Doesn't Flatten Language -- It Restructures It: Surface Markers Amplify While Deep Syntax Dies

arXiv:2605.20602v1 Announce Type: new Abstract: Successive self-training on a language model's own outputs is widely characterized as a process of flattening: diversity drops, distributions narrow, an

Single-Pass, Depth-Selective Reading for Multi-Aspect Sentiment Analysis

arXiv:2605.20998v1 Announce Type: new Abstract: Aspect-Term Sentiment Analysis (ATSA) in multi-aspect sentences faces a fundamental tradeoff between efficiency and expressiveness. Existing models eith