Search: “research”

Adversarial Training Without Input Gradients via Low-Rank Householder Expansions

arXiv:2608.26963v1 Announce Type: new Abstract: This work concerns adversarial training against the small-norm adversarial examples that arise from the inherent input instability of a trained deep neu

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Research

AffectOmni: RL-Verifiable People-Centric Grounded Affective Reasoning for Social and Art-Related Scenes

DGX agent

arXiv:2608.26193v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) achieve strong performance on VQA and scene understanding, yet affective reasoning remains vulnerable to shortc

researcharxiv-cs-ai

28 Aug 2026

Affix Cache for Diffusion Large Language Models

arXiv:2608.26140v1 Announce Type: new Abstract: Diffusion Large Language Models (DLLMs) enable non-autoregressive decoding and bidirectional context modeling, but efficient inference remains challengi

Algebraic Multigrid Acceleration for Efficient Label Spreading

arXiv:2608.26309v1 Announce Type: new Abstract: Modern machine learning models rely on large amounts of labeled data. However, manual annotation of large-scale datasets is expensive and time-consuming

Algorithmic Principles For Multiclass Learning Are Hard To Come By: Limits of Regularization and Proper Learning

arXiv:2608.26516v1 Announce Type: new Abstract: Two of the most fundamental questions in statistical learning theory are the following: which prediction problems are learnable, and how should they be

Arbitrary-Order Hermite Interpolation of Rigid-Motion Jets via Hyper-Multidual Quaternions

arXiv:2608.27000v1 Announce Type: new Abstract: We study bilateral interpolation of finite-order rigid-motion jets represented by unit dual quaternions. An order-n multidual (MD) algebra is the trunca

researcharxiv-cs-ro

Artificial Intelligence Models Can Predict and Collaboratively Modulate Human Memory Search

arXiv:2608.26152v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit unprecedented natural language generation and many text-based problem-solving capabilities. Indeed, in many langu

Attention-Guided Reliability Scaling for Contrastive Decoding in Robust Audio-Visual Speech Recognition

arXiv:2608.26213v1 Announce Type: cross Abstract: Large language model (LLM)-based audio-visual speech recognition (AVSR) systems are robust under noise. Contrastive decoding (CD), originally introduc

Automated 2D and 3D Segmentation of AMD and DME Lesions in OCT

arXiv:2608.27095v1 Announce Type: new Abstract: Age-related macular degeneration (AMD) and diabetic macular edema (DME) are leading causes of vision loss, and optical coherence tomography (OCT) is the

Beyond Discrete Samples: High Information Density Replay for Efficient Lifelong Person Re-Identification

arXiv:2508.01587v4 Announce Type: replace Abstract: Lifelong Person Re-Identification (LReID) typically resists catastrophic forgetting by replaying historical samples, rehearsing domain distributions

Beyond Linearization: Attributed Table Graphs for Table Reasoning

arXiv:2601.08444v2 Announce Type: replace Abstract: Table reasoning, a task to answer questions by reasoning over data presented in tables, is an important topic due to the prevalence of knowledge sto

Beyond the Rosetta Stone: Unification Forces in Generalization Dynamics

arXiv:2508.11017v3 Announce Type: replace-cross Abstract: Large language models (LLMs) struggle with cross-lingual knowledge transfer: they sometimes hallucinate when asked in one language about facts

Bridging short- and medium-range weather forecasting with machine learning

arXiv:2608.26822v1 Announce Type: cross Abstract: The National Oceanic and Atmospheric Administration (NOAA) employs independent prediction systems for distinct forecast products. While some separatio

C-Unseen: Weak Signal Detection in Dynamic Temporal Knowledge Graphs via LLM Reasoning

arXiv:2608.26870v1 Announce Type: new Abstract: Weak signals are early, low-visibility indicators that precede significant changes before those changes become established. Existing detection methods,

Can a Model Catch Its Own Hallucinations for Free?: Label-Free Doubt Signals Hold Their Own Against a Labelled Dataset for Abstention

arXiv:2608.26121v1 Announce Type: new Abstract: Large language models state false facts as fluently as true ones, yet a model often 'knows' internally when it is on shaky ground: the probability it as

Can You Say This for Me? Speaking Up by Proxy in Co-Located Discussion

arXiv:2608.26185v1 Announce Type: new Abstract: Equal participation in co-located discussion is important for effective collaboration, yet people often hold back when they anticipate negative interper

Cascaded Batch Prompting

arXiv:2608.27038v1 Announce Type: new Abstract: Although batch prompting makes large language model inference more efficient by processing multiple instances simultaneously, it suffers from unpredicta

Chart2SVG: Editable SVG Generation from Raster Chart Images

arXiv:2608.26544v1 Announce Type: new Abstract: We present Chart2SVG, a multimodal large language model that converts static raster charts into structurally organized, semantically enriched SVGs that

Circuit Condensation: Post-Training that Concentrates a Behavior's Causal Circuit

arXiv:2608.27254v1 Announce Type: new Abstract: One approach to mechanistic interpretability explains behavior through circuits: the components and connections that carry it. Frozen discovery often re

Clinically Aligned Geometry Constraints for Robust IVUS Vessel Boundary Segmentation

arXiv:2606.18723v2 Announce Type: replace Abstract: Intravascular ultrasound (IVUS) lumen and external elastic membrane (EEM) segmentation is important for quantitative coronary plaque burden assessme

ClusterAttention: A training-free speedup of bidirectional attention

arXiv:2608.26965v1 Announce Type: cross Abstract: This paper introduces ClusterAttention, a general training-free speedup of bidirectional attention layers. Existing sparse attention methods either re

Co-Evolving Structured Knowledge and Reasoning in Language Models

arXiv:2608.26386v1 Announce Type: cross Abstract: Retrieval-augmented methods improve factual accuracy by grounding language models in external knowledge, but retrieving over unstructured text often i

CoGeo-GS: Concept-Driven and Geometry-Aware Multi-Object Removal in 3D Scenes

arXiv:2608.26656v1 Announce Type: cross Abstract: Multi-object removal in 3D scenes is challenging due to severe occlusions, semantic entanglement, and the difficulty of maintaining geometric and mult

Common Geodesics Do Not Guarantee Fisher Consistency of the Structured SVM: Minimal Counterexamples and a Tree-Metric Classification

arXiv:2608.27203v1 Announce Type: new Abstract: A known necessary condition for Fisher consistency of the structured support vector machine requires the task loss to be a metric for which every output

Comparing Chunking and Embedding Strategies for Turkish RAG Systems

arXiv:2608.26192v1 Announce Type: cross Abstract: How documents are segmented into retrievable chunks and how those chunks are embedded strongly affect Retrieval-Augmented Generation (RAG) quality, ye

Compositional Generalization via Structural Identification in a Category-Theoretic Framework

arXiv:2608.26465v1 Announce Type: new Abstract: Compositional generalization is usually evaluated through model accuracy. We instead ask which structural or lexical identifications make held-out COGS

Cone Extended Rayleigh Quotients for Directed Graph Learning: Minimax Spectral Certificates, Sensitivity, and Adaptive Control

arXiv:2608.27122v1 Announce Type: new Abstract: Directed graph learning naturally leads to trainable nonsymmetric propagation operators with distinct right and left spectral structures. Building on th

Constraint-Aware Physics-Informed Neural Networks for Static Shape Estimation of Co-Manipulative Continuum Robots

arXiv:2608.26273v1 Announce Type: cross Abstract: Static shape estimation of co-manipulative continuum robots (CCRs) is challenging because the continuum arms and manipulated flexible object form a cl

CounterVid: Counterfactual Video Generation for Mitigating Action and Temporal Hallucinations in Video-Language Models

arXiv:2601.04778v2 Announce Type: replace-cross Abstract: Video-language models (VLMs) achieve strong multimodal understanding but remain prone to hallucinations, especially when reasoning about actio

CPGRec+: A Balance-oriented Framework for Personalized Video Game Recommendations

arXiv:2604.14586v4 Announce Type: replace-cross Abstract: The rapid expansion of gaming industry requires advanced recommender systems tailored to its dynamic landscape. Existing Graph Neural Network

CritICL: Inference-Time Weak-to-Strong Generalization from Small Language Model Failure Modes

arXiv:2608.27455v1 Announce Type: new Abstract: Recent advances in inference-time scaling have significantly improved the reasoning performance of large language models (LLMs). However, these methods

Data-driven Koopman mode approximation: A neural power iteration algorithm

arXiv:2608.26943v1 Announce Type: cross Abstract: This paper proposes a novel data-driven algorithm to approximate the dominant eigenfunctions (aka.~modes) of the Koopman operator of nonlinear dynamic

Data-efficient crack quantification in lithium-ion cathodes using foundation model transfer

arXiv:2608.27162v1 Announce Type: cross Abstract: Battery lifetime is central to sustainable electrification, yet the particle cracking that drives lithium-ion cathode aging is hard to measure: quanti

Data Science Approaches to Evaluating Honours Candidates

arXiv:2608.26135v1 Announce Type: new Abstract: We present a modular data-science pipeline for estimating public sentiment towards individuals from fragmented, unstructured open-source intelligence (O

Decentralized Multitask Learning over Learned Task Graphs

arXiv:2608.26989v1 Announce Type: new Abstract: This paper investigates decentralized multitask learning over networks when the underlying task relationships are unknown. While existing graph-regulari

Decoupled I/O-Dominant Pipelines for Large-Scale Whole-Slide Image Embedding Extraction

arXiv:2608.27278v1 Announce Type: cross Abstract: Whole-slide images (WSIs) are central to computational pathology but are prohibitively large, making patch-based processing the practical unit for fou

Dependency-Aware Revocable Decoding for Efficient Diffusion Large Language Model Inference

arXiv:2608.26574v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) offer a promising alternative to autoregressive generation by decoding multiple tokens in parallel through itera

Differentiable Jitter Correction using Deep Learning-based Image Quality Metric for Phase-Contrast Micro-CT

arXiv:2608.27034v1 Announce Type: new Abstract: This paper proposes a fully differentiable jitter correction method for X-ray phase-contrast micro computed tomography using a deep learning-based image

DINOcular: Self-Supervised Visuospatial Representations

arXiv:2608.27226v1 Announce Type: new Abstract: We introduce a self-supervised framework for learning joint visuospatial representations from RGB-D observations. While modern vision foundation models

Discovering Relationships in Data Lakes Using Large Language Models: An Industrial Case

arXiv:2608.26750v1 Announce Type: new Abstract: Data lakes rely on metadata to remain usable, yet this meta data is often limited or weakly informative for column relationship discovery, especially in

Dispersive Forward Tree Search for Optimal Control: Coverage, Complexity, and Computation

arXiv:2608.26314v1 Announce Type: new Abstract: Steering-based planners require solutions to state-to-state boundary value problems, which can be inaccessible for nonlinear platforms. Forward propagat

researcharxiv-cs-ro

District-Level Food Environment Indicators and Social Vulnerability in Sao Paulo

arXiv:2608.26299v1 Announce Type: cross Abstract: Urban food environments may reflect broader socioeconomic inequalities, but district-level evidence remains limited in Brazilian cities. This study ex

Dose-PlanNet: Physics Based Radiotherapy Dose Prediction with Deep Learning

arXiv:2608.26901v1 Announce Type: cross Abstract: Automating prostate radiotherapy treatment planning is dosimetrically complex, particularly for extreme hypofractionated regimens. In this study, we i

EditaLive! Unified Character Video Editing for Live Streaming

arXiv:2608.27123v1 Announce Type: new Abstract: Conventional video editing primarily focuses on scene-level content, whereas live streaming places greater emphasis on the human subject. However, direc

EEG-to-Report: An Annotation and Feature-Text Framework for Training Language Models on Clinical EEG

arXiv:2608.26153v1 Announce Type: new Abstract: Clinical electroencephalography (EEG) reporting remains largely manual and time-consuming, and current EEG software ecosystems do not produce the struct

Enforcing Dirichlet Boundary Conditions in Operator Learning

arXiv:2608.27256v1 Announce Type: cross Abstract: Operator learning in scientific machine learning is concerned with approximation of maps between infinite-dimensional function spaces; such maps frequ

Equal Ranking Quality, Different Decisions: Training Order-Consistent LLM Scorers

arXiv:2608.26762v1 Announce Type: new Abstract: Rerankers, reward models and multi-document QA scorers score candidate documents or responses in one LLM prompt, so each score depends on their order. S

FaultLens: Learning Compact Behavioral Test Suites for Generated Operational Programs

arXiv:2608.26746v1 Announce Type: cross Abstract: Generated operational programs are often validated with either a few hand-written examples or exhaustive regression suites. The former can miss sparse