Search: “research”

A Data-Free Physics-Informed Neural Operator for Level-Set Interface Advection

arXiv:2609.38195v1 Announce Type: new Abstract: Operators for interfacial problems are trained on reference solutions produced by the solver they are intended to replace. This work develops a data-fre

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A differentiability framework for zigzag persistent homology via linear interpolation

DGX agent

arXiv:2609.39242v1 Announce Type: new Abstract: Persistent homology can be differentiated and incorporated into learning pipelines, but no analogous framework exists for zigzag persistence, which is n

researcharxiv-cs-lg

1 Oct 2026

A Flow Matching Algorithm for Many-Shot Adaptation to Unseen Distributions

arXiv:2605.06272v2 Announce Type: replace Abstract: While generative modeling has achieved remarkable success on tasks like natural language-conditioned image generation, enabling model adaptation fro

A Generalisation Signal Need Not Be a Model-Selection Signal

arXiv:2609.39099v1 Announce Type: cross Abstract: Model selection in computational biology often relies on validation data drawn from the training regime, even when deployment lies outside it. When va

A Generalizable and Explainable Framework for Synthetic Video Detection Using First-Digit Gradient Statistics

arXiv:2609.39585v1 Announce Type: new Abstract: AI video generators have not only become harder to detect but are used to generate a diverse set of scenarios from landscapes to street views to animal

A library for differentiable signal processing and machine learning on the sphere

arXiv:2609.39737v1 Announce Type: new Abstract: The two-dimensional sphere embedded in three-dimensional Euclidean space S2, plays a central role in a variety of scientific and engineering domains, in

A Moving-Horizon Approximate Branch-and-Reduce Method for Deep Classification Trees

arXiv:2609.38194v1 Announce Type: cross Abstract: Despite the importance for interpretability, decision trees face severe scalability challenges. Existing global optimal methods are often limited by b

A polynomial time algebraic solution to exact marginal inference in Markov Random Field models

arXiv:1709.09051v3 Announce Type: replace-cross Abstract: This paper develops on algebraic grounds a polynomial time exact linear solution to the hard combinatorial problem of marginal inference in Ma

A strategic roadmap for an atomistic machine-learning ecosystem

arXiv:2609.39090v1 Announce Type: cross Abstract: Data-driven machine learning (ML) techniques have become an essential tool in many domains of science. Their application to atomistic simulations of m

A Tilted Bowl Is Not a Slippery Slope: Compressing Looped Models

arXiv:2609.39277v1 Announce Type: cross Abstract: Looped models reason by applying the same block of weights many times, so compressing that block saves memory traffic on every loop. Compressed looped

researcharxiv-cs-cl

Acceleration of Diffusion Language Model through Discrete Average Generator

arXiv:2609.38364v1 Announce Type: cross Abstract: Discrete diffusion models and flow matching have emerged as powerful frameworks for generative modeling over discrete state spaces, yet efficient few-

Adaptive Self-Consistency: From Black-Box Sampling to Distribution-Valued Feedback

arXiv:2609.38931v1 Announce Type: cross Abstract: Self-consistency samples many reasoning trajectories and aggregates their final answers, treating the LLM as a black box that returns one answer per t

Adaptive Spectral Feature Forecasting for Diffusion Sampling Acceleration

arXiv:2603.01623v2 Announce Type: replace Abstract: Diffusion models have become the dominant tool for high-fidelity image and video generation, yet are critically bottlenecked by their inference spee

Airfoil2Vec: Spectral Geometry-Conditioned Neural Surrogate Models for Airfoil Aerodynamics and a Downforce-Generating CFD Dataset

arXiv:2609.38213v1 Announce Type: cross Abstract: We introduce a dataset of approximately 10,000 Reynolds-Averaged Navier-Stokes (RANS) simulations of steady, incompressible, two-dimensional subsonic

Algorithmic Recourse Under Competition

arXiv:2609.39877v1 Announce Type: cross Abstract: Algorithmic recourse provides individuals who have received undesirable outcomes from machine learning models with suggestions for minimum-cost improv

Aligning Thoughts with Answers: Probability Rewards to Tame Thinking Drift

arXiv:2609.39183v1 Announce Type: new Abstract: This paper studies extbf{thinking--answer consistency} in vision-language models. We focus on Visual Intention Grounding, where a model infers a target

Alleviating Hallucination in Reasoning Tasks with Training-Free Uncertainty-Guided Steering

arXiv:2609.38962v1 Announce Type: new Abstract: Recent work on hallucination detection in large language models has shown that, for a fixed pre-trained model and reasoning task, it is possible to esti

Also Small Models Can Reasonably Self-Evaluate Their Confidence

arXiv:2609.39478v1 Announce Type: new Abstract: This study systematically evaluates self-evaluation-based uncertainty quantification across different language models of varying sizes on question-answe

Amortized Bayesian Inference on Multilevel Models of Arbitrary Structure

arXiv:2609.40024v1 Announce Type: cross Abstract: We develop a general method for amortized Bayesian inference on multilevel models of arbitrary structure. Given a generative model specified as a dire

An Uncertainty-Guided Digital Twin Framework for Online Adaptive Proton Therapy in Head and Neck Cancer: A Feasibility Study

arXiv:2609.39010v1 Announce Type: cross Abstract: Objective: Head and neck (HN) proton therapy spans six to seven weeks of anatomical change, while offline replanning takes about a week. We present an

Anchoring Adversarial Trajectories to Data Manifolds: A Bilevel Transfer Optimization Framework

arXiv:2609.38991v1 Announce Type: cross Abstract: A key bottleneck in adversarial transfer is a trajectory-level geometric disconnect: ambient gradients often drift away from the intrinsic data manifo

Aperture: Training-Free Multiscale Concept Bottlenecks for Remote Sensing

arXiv:2609.38603v1 Announce Type: new Abstract: While earth observation models have advanced substantially, they still lack interpretability. While concept-bottleneck models provide interpretability a

Association profile conditioning in a set-temporal transformer for cross-session intracortical motor decoding

arXiv:2609.39080v1 Announce Type: cross Abstract: Intracortical motor decoders degrade across sessions because the set of recorded units changes and persisting units can alter how their firing relates

Average-and Last-Iterate Lower Bounds for Optimistic Matrix Mirror-Prox in Quantum Zero-Sum Games

arXiv:2609.38835v1 Announce Type: cross Abstract: Optimistic matrix mirror-prox (OMMP) computes epsilon-approximate Nash equilibria in quantum zero-sum games with an O(1/arepsilon) average-iterate gua

BadAction: Backdoor Attacks on Interactive Video Generation via Action-Guided Triggers

arXiv:2609.39047v1 Announce Type: new Abstract: Interactive video generation (IVG) models have achieved remarkable progress in producing controllable visual content guided by user-defined actions, yet

Bandits with Multiple Optimal Arms: Minimax Regret and Non-Adaptivit

arXiv:2609.38659v1 Announce Type: cross Abstract: We study multi-armed bandits (MAB) with multiple optimal arms, motivated by the fact that many practical decision making problems admit multiple corre

BELIEFRAG: Making Adaptive RAG State-Aware under Evolving Evidence

arXiv:2609.39139v1 Announce Type: new Abstract: Adaptive RAG uses signals such as confidence, relevance, support, and retrieval quality to decide when to search or correct evidence. In multi-step retr

Beyond Local Linearity: Scale-Resolved Geometry of Learned Image Encoders

arXiv:2609.39115v1 Announce Type: new Abstract: Understanding how learned representations respond to finite input changes is important for characterizing their sensitivity, invariances, and robustness

Beyond Mode Collapse: Generating Diverse Synthetic Expert Conversations via Generative Flow Networks

arXiv:2609.38359v1 Announce Type: new Abstract: High quality synthetic data is central to post training LLMs for adaptive AI applications that represent the diverse expert strategies and decisions in

Beyond Rephrasing: Book-Level Organization Improves Synthetic Textbook Data for Mid-Training

arXiv:2607.28109v2 Announce Type: replace Abstract: Synthetic textbook data has improved language model pre-training, but prior work largely treats the benefit as a property of generated content or lo

Beyond the Commitment Boundary: Probing Epiphenomenal Chain-of-Thought in Large Reasoning Models

arXiv:2606.13603v2 Announce Type: replace-cross Abstract: Chain-of-thought (CoT) reasoning is the dominant paradigm for inference-time scaling in language models, yet the causal influence of individua

Beyond the Current Scene: Event-Referential Grasping with Active View Selection

arXiv:2609.39375v1 Announce Type: cross Abstract: A robot that observes people interacting with objects should be able to carry out later requests that refer back to those interactions. Such requests

Beyond Uncertainty Sets: Leveraging Optimal Transport to Extend Conformal Predictive Distributions to Multivariate Settings

arXiv:2511.15146v2 Announce Type: replace-cross Abstract: Conformal prediction (CP) constructs uncertainty sets for model outputs with finite-sample coverage guarantees. Yet ranking scores is straight

Bounded Channel-Adaptive Spectral Learning for Forward-Consistent Inverse Flapping-Wing Aerodynamics

arXiv:2609.38730v1 Announce Type: new Abstract: Flapping-wing vehicles regulate aerodynamic forces and moments through coordinated variations in stroke, deviation, and pitch motion. Because the result

researcharxiv-cs-ro

Budget Boundary Effects in Test-Time Mathematical Reasoning

arXiv:2609.38699v1 Announce Type: new Abstract: A cumulative token cap can fall inside a mathematical derivation, forcing a test-time controller to choose between stopping at the cap (strict) and allo

C-STRIDE: An Observation-Driven AI Digital Twin for Predicting Basin-Wide Flood Fields from Sparse Stream-Gauge Histories

arXiv:2609.39005v1 Announce Type: new Abstract: Emergency managers need to know where floodwater is, how deep it is, and how it will change over the coming hours across an entire river basin. During a

CAMOS: Coupled Oscillatory State-Space Model for Multimodal Clinical Time-Series

arXiv:2609.39484v1 Announce Type: cross Abstract: Longitudinal clinical cohorts are multimodal, irregularly sampled and pervasively incomplete: in ADNI, positron emission tomography and cerebrospinal

Can Domain Generalization be Guaranteed in Small-Sample Learning?

arXiv:2609.39512v1 Announce Type: new Abstract: The small-sample learning problem remains a fundamental challenge in machine learning because limited training data lead to unstable model estimation an

Can We Anticipate Violence? Multimodal Learning from Pre-Incident Behavioral Cues

arXiv:2609.40014v1 Announce Type: new Abstract: Detecting violence after it begins is important from recognizing behavioral cues that appear immediately beforehand. This work studies short-horizon pre

CAS II: Symmetric Partitions as Kolmogorov Models

arXiv:2609.40290v1 Announce Type: cross Abstract: In algorithmic statistics a string x is explained by a finite set containing it, and Kolmogorov's structure function records the smallest such model a

Centralized Multi-UAV Exploration and 3D Reconstruction Using Single-UAV Planners

arXiv:2609.40208v1 Announce Type: new Abstract: Extending single Unmanned Aerial Vehicles (UAVs) exploration methods to multi-UAV teams can improve coverage speed and robustness, but introduces challe

researcharxiv-cs-ro

Certifying Residual Architectures from Their Primitives: A Sharp Stability Threshold

arXiv:2607.14576v2 Announce Type: replace Abstract: Whether a deep residual architecture trains stably is usually determined by training it, which is expensive and answers the question only for the ar

Characterizing Questioning Patterns and Student Engagement Through Contextual Analysis of Real-Time Classroom Interactions

arXiv:2609.38907v1 Announce Type: cross Abstract: Real-time classroom polling is now routine, yet the data it produces is usually read narrowly, as a correctness score or a headcount. Such readings sa

ChartRevise: A Dataset and Evaluation Protocol for Exact Chart Editing via Code

arXiv:2609.38642v1 Announce Type: new Abstract: Chart editing requires cross-modal edit grounding, realizing a requested visual change in the code that draws it, with necessary related updates and wit

Communication-Free Distributed Multi-Robot Task Allocation under Partial Observations Using Labeled Multi-Bernoulli Filtering

arXiv:2609.39416v1 Announce Type: new Abstract: This paper proposes a communication-free multi-robot task allocation framework based solely on local observations. In this study, tasks are defined as r

researcharxiv-cs-ro

Compact Language, Complex Model Shifts: How and Where Ambiguity and Underspecification Affect LLMs

arXiv:2609.39572v1 Announce Type: new Abstract: We analyze how lexical ambiguity and underspecification affect language model training. We create artificial homonyms and artificial hypernyms as pseudo

researcharxiv-cs-cl

Completion-Aware Cross-Fidelity Offline-to-Online Reinforcement Learning for Multi-Line Bus Holding

arXiv:2609.39868v1 Announce Type: new Abstract: Exploratory reinforcement learning (RL) on an operating bus fleet is impractical,while policies trained only from historical data cannot acquire new exp

Component-Weighted Centroid Search for Exact Incremental BPE

arXiv:2609.40016v1 Announce Type: cross Abstract: Exact incremental BPE maintains the canonical tokenization state after every appended byte. The recent algorithm of Jiang and Gong (2026) does this in