Search: “research”

NPU Design for Diffusion Language Model Inference

arXiv:2601.20706v2 Announce Type: replace-cross Abstract: Diffusion-based LLMs (dLLMs) fundamentally depart from traditional autoregressive (AR) LLM inference: they leverage bidirectional attention, b

On the algebra of Koopman eigenfunctions and on some of their infinities

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DGX agent

arXiv:2604.21825v1 Announce Type: cross Abstract: For continuous-time dynamical systems with reversible trajectories, the nowhere-vanishing eigenfunctions of the Koopman operator of the system form a

researcharxiv-cs-lg

24 Apr 2026

On the Relationship between Bayesian Networks and Probabilistic Structural Causal Models

arXiv:2603.27406v2 Announce Type: replace Abstract: In this paper, the relationship between probabilistic graphical models, in particular Bayesian networks, and causal diagrams, also called structural

Optimal Aggregation of LLM and PRM Signals for Efficient Test-Time Scaling

arXiv:2510.13918v2 Announce Type: replace Abstract: Process reward models (PRMs) are a cornerstone of test-time scaling (TTS), designed to verify and select the best responses from large language mode

PanGuide3D: Cohort-Robust Pancreas Tumor Segmentation via Probabilistic Pancreas Conditioning and a Transformer Bottleneck

arXiv:2604.20981v1 Announce Type: cross Abstract: Pancreatic tumor segmentation in contrast-enhanced computed tomography (CT) is clinically important yet technically challenging: lesions are often sma

Partially Lazy Gradient Descent for Smoothed Online Learning

arXiv:2601.15984v2 Announce Type: replace Abstract: We introduce extsc{k-lazyGD}, an online learning algorithm that bridges the gap between greedy Online Gradient Descent (OGD, for k{=}1) and lazy GD/

PAT3D: Physics-Augmented Text-to-3D Scene Generation

arXiv:2511.21978v2 Announce Type: replace Abstract: We introduce PAT3D, the first physics-augmented text-to-3D scene generation framework that integrates vision-language models with physics-based simu

PDGMM-VAE: A Variational Autoencoder with Adaptive Per-Dimension Gaussian Mixture Model Priors for Nonlinear ICA

arXiv:2603.23547v2 Announce Type: replace-cross Abstract: Independent component analysis is a core framework within blind source separation for recovering latent source signals from observed mixtures

PercHead: Perceptual Head Model for Single-Image 3D Head Reconstruction & Editing

arXiv:2511.02777v2 Announce Type: replace Abstract: We present PercHead, a model for single-image 3D head reconstruction and disentangled 3D editing - two tasks that are inherently challenging due to

Phonological Subspace Collapse Is Aetiology-Specific and Cross-Lingually Stable: Evidence from 3,374 Speakers

arXiv:2604.21706v1 Announce Type: new Abstract: We previously introduced a training-free method for dysarthria severity assessment based on d-prime separability of phonological feature subspaces in fr

Planning Beyond Text: Graph-based Reasoning for Complex Narrative Generation

arXiv:2604.21253v1 Announce Type: cross Abstract: While LLMs demonstrate remarkable fluency in narrative generation, existing methods struggle to maintain global narrative coherence, contextual logica

PLAS-Net: Pixel-Level Area Segmentation for UAV-Based Beach Litter Monitoring

arXiv:2604.21313v1 Announce Type: new Abstract: Accurate quantification of the physical exposure area of beach litter, rather than simple item counts, is essential for credible ecological risk assessm

Post-Training Augmentation Invariance

arXiv:2505.11702v2 Announce Type: replace Abstract: This work develops a framework for post-training augmentation invariance, in which our goal is to add invariance properties to a pretrained network

Pre-process for segmentation task with nonlinear diffusion filters

arXiv:2604.21422v1 Announce Type: new Abstract: This paper deals with the case of using nonlinear diffusion filters to obtain piecewise constant images as a previous process for segmentation technique

Pre-trained LLMs Meet Sequential Recommenders: Efficient User-Centric Knowledge Distillation

arXiv:2604.21536v1 Announce Type: cross Abstract: Sequential recommender systems have achieved significant success in modeling temporal user behavior but remain limited in capturing rich user semantic

Predicting Scale-Up of Metal-Organic Framework Syntheses with Large Language Models

arXiv:2604.20899v1 Announce Type: cross Abstract: Scalable synthesis remains the gate between MOF discovery and industrial deployment, as scale-up know-how is fragmented across disparate reports. We i

Preferences of a Voice-First Nation: Large-Scale Pairwise Evaluation and Preference Analysis for TTS in Indian Languages

arXiv:2604.21481v1 Announce Type: new Abstract: Crowdsourced pairwise evaluation has emerged as a scalable approach for assessing foundation models. However, applying it to Text to Speech(TTS) introdu

Prefix Parsing is Just Parsing

arXiv:2604.21191v1 Announce Type: new Abstract: Prefix parsing asks whether an input prefix can be extended to a complete string generated by a given grammar. In the weighted setting, it also provides

Preserving Knowledge in Large Language Model with Model-Agnostic Self-Decompression

arXiv:2406.11354v3 Announce Type: replace-cross Abstract: Humans can retain old knowledge while learning new information, but Large Language Models (LLMs) often suffer from catastrophic forgetting whe

Probably Approximately Consensus: On the Learning Theory of Finding Common Ground

arXiv:2604.21811v1 Announce Type: cross Abstract: A primary goal of online deliberation platforms is to identify ideas that are broadly agreeable to a community of users through their expressed prefer

Projected Gradient Unlearning for Text-to-Image Diffusion Models: Defending Against Concept Revival Attacks

arXiv:2604.21041v1 Announce Type: new Abstract: Machine unlearning for text-to-image diffusion models aims to selectively remove undesirable concepts from pre-trained models without costly retraining.

Prototype-Based Test-Time Adaptation of Vision-Language Models

arXiv:2604.21360v1 Announce Type: new Abstract: Test-time adaptation (TTA) has emerged as a promising paradigm for vision-language models (VLMs) to bridge the distribution gap between pre-training and

ReaGeo: Reasoning-Enhanced End-to-End Geocoding with LLMs

arXiv:2604.21357v1 Announce Type: new Abstract: This paper proposes ReaGeo, an end-to-end geocoding framework based on large language models, designed to overcome the limitations of traditional multi-

Relocation of compact sets in R^n by diffeomorphisms and linear separability of datasets in R^n

arXiv:2604.21393v1 Announce Type: new Abstract: Relocation of compact sets in an n-dimensional manifold by self-diffeomorphism is of its own interest as well as significant potential applications to d

Replay-buffer engineering for noise-robust quantum circuit optimization

arXiv:2604.21863v1 Announce Type: cross Abstract: Deep reinforcement learning (RL) for quantum circuit optimization faces three fundamental bottlenecks: replay buffers that ignore the reliability of t

Reversible Deep Learning for 13C NMR in Chemoinformatics: On Structures and Spectra

arXiv:2602.03875v4 Announce Type: replace-cross Abstract: We introduce a reversible deep learning model for 13C NMR that uses a single conditional invertible neural network for both directions between

Revisiting Non-Verbatim Memorization in Large Language Models: The Role of Entity Surface Forms

arXiv:2604.21882v1 Announce Type: new Abstract: Understanding what kinds of factual knowledge large language models (LLMs) memorize is essential for evaluating their reliability and limitations. Entit

RV-HATE: Reinforced Multi-Module Voting for Implicit Hate Speech Detection

arXiv:2510.10971v2 Announce Type: replace-cross Abstract: Hate speech remains prevalent in human society and continues to evolve in its forms and expressions. Modern advancements in internet and onlin

Scensory: Real-Time Robotic Olfactory Perception for Joint Identification and Source Localization

arXiv:2509.19318v2 Announce Type: replace-cross Abstract: While robotic perception has advanced rapidly in vision and touch, enabling robots to reason about indoor fungal contamination from weak, diff

researcharxiv-cs-ro

Schoenfeld's Anatomy of Mathematical Reasoning by Language Models

arXiv:2512.19995v2 Announce Type: replace-cross Abstract: Large language models increasingly expose reasoning traces, yet their underlying cognitive structure and steps remain difficult to identify an

Model Releases

SCM: Sleep-Consolidated Memory with Algorithmic Forgetting for Large Language Models

model-releasesarxiv-cs-lg

arXiv:2604.20943v1 Announce Type: new Abstract: We present SCM (Sleep-Consolidated Memory), a research preview of a memory architecture for large language models that draws on neuroscientific principl

Sculpt4D: Generating 4D Shapes via Sparse-Attention Diffusion Transformers

arXiv:2604.21592v1 Announce Type: new Abstract: Recent breakthroughs in 3D generative modeling have yielded remarkable progress in static shape synthesis, yet high-fidelity dynamic 4D generation remai

SDNGuardStack: An Explainable Ensemble Learning Framework for High-Accuracy Intrusion Detection in Software-Defined Networks

arXiv:2604.20934v1 Announce Type: cross Abstract: Software-Defined Networking (SDN) is another technology that has been developing in the last few years as a relevant technique to improve network prog

SemanticAgent: A Semantics-Aware Framework for Text-to-SQL Data Synthesis

arXiv:2604.21414v1 Announce Type: new Abstract: Existing text-to-SQL synthesis pipelines still conflate executability with semantic validity: syntactic checks and execution-based validation can retain

SemEval-2026 Task 4: Narrative Story Similarity and Narrative Representation Learning

arXiv:2604.21782v1 Announce Type: new Abstract: We present the shared task on narrative similarity and narrative representation learning - NSNRL (pronounced 'nass-na-rel'). The task operationalizes na

SGD at the Edge of Stability: The Stochastic Sharpness Gap

arXiv:2604.21016v1 Announce Type: cross Abstract: When training neural networks with full-batch gradient descent (GD) and step size eta, the largest eigenvalue of the Hessian -- the sharpness S(oldsym

Sink-Token-Aware Pruning for Fine-Grained Video Understanding in Efficient Video LLMs

arXiv:2604.20937v1 Announce Type: new Abstract: Video Large Language Models (Video LLMs) incur high inference latency due to a large number of visual tokens provided to LLMs. To address this, training

Slot Machines: How LLMs Keep Track of Multiple Entities

arXiv:2604.21139v1 Announce Type: new Abstract: Language models must bind entities to the attributes they possess and maintain several such binding relationships within a context. We study how multipl

Spatio-temporal probabilistic forecast using MMAF-guided learning

arXiv:2603.15055v2 Announce Type: replace-cross Abstract: We present a theory-guided generalized Bayesian methodology for spatio-temporal raster data, which we use to train an ensemble of stochastic f

Spectral Kernel Dynamics for Planetary Surface Graphs: Distinction Dynamics and Topological Conservation

arXiv:2604.20887v1 Announce Type: cross Abstract: The spectral kernel field equation R[k] = T[k] lacks a conservation-law analog. We prove (i) the fixed-point flow is strictly volume-expanding (tr DF

SPIRE: Structure-Preserving Interpretable Retrieval of Evidence

arXiv:2604.20849v1 Announce Type: cross Abstract: Retrieval-augmented generation over semi-structured sources such as HTML is constrained by a mismatch between document structure and the flat, sequenc

StegoStylo: Squelching Stylometric Scrutiny through Steganographic Stitching

arXiv:2601.09056v3 Announce Type: replace-cross Abstract: Stylometry--the identification of an author through analysis of a text's style (i.e., authorship attribution)--serves many constructive purpos

StructMem: Structured Memory for Long-Horizon Behavior in LLMs

arXiv:2604.21748v1 Announce Type: cross Abstract: Long-term conversational agents need memory systems that capture relationships between events, not merely isolated facts, to support temporal reasonin

Sub-Token Routing in LoRA for Adaptation and Query-Aware KV Compression

arXiv:2604.21335v1 Announce Type: cross Abstract: Sub-token routing offers a finer control axis for transformer efficiency than the coarse units used in most prior work, such as tokens, pages, heads,

TAPO-Description Logic for Information Behavior: Refined OBoxes, Inference, and Categorical Semantics

arXiv:2604.21172v1 Announce Type: cross Abstract: This paper develops a refined version of TAPO-description logic for the analysis of information behavior. The framework is treated not as a single hom

Ternary Memristive Logic: Hardware for Reasoning Realized via Domain Algebra

arXiv:2604.20891v1 Announce Type: cross Abstract: Memristive crossbars store numerical weights needing aggregation and decoding; a single junction means nothing alone. This paper presents a fundamenta

The CriticalSet problem: Identifying Critical Contributors in Bipartite Dependency Networks

arXiv:2604.21537v1 Announce Type: new Abstract: Identifying critical nodes in complex networks is a fundamental task in graph mining. Yet, methods addressing an all-or-nothing coverage mechanics in a

The Sample Complexity of Multicalibration

arXiv:2604.21923v1 Announce Type: new Abstract: We study the minimax sample complexity of multicalibration in the batch setting. A learner observes n i.i.d. samples from an unknown distribution and mu