Search: “models”

arXiv:2602.21204v3 Announce Type: replace-cross Abstract: Test-time training (TTT) with KV binding as sequence modeling layer is commonly interpreted as a form of online meta-learning that memorizes a

hardwarearxiv-cs-cv

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Model Releases

The TTS-STT Flywheel: Synthetic Entity-Dense Audio Closes the Indic ASR Gap Where Commercial and Open-Source Systems Fail

DGX agent

arXiv:2605.03073v1 Announce Type: new Abstract: Niche-domain Indic ASR -- digit strings, currency amounts, addresses, brand names, English/Indic codemix -- is under-served by both open-source SOTA and

model-releasesarxiv-cs-cl

6 May 2026

Training-Free Probabilistic Time-Series Forecasting with Conformal Seasonal Pools

arXiv:2605.03789v1 Announce Type: cross Abstract: We propose Conformal Seasonal Pools (CSP), a training-free probabilistic time-series forecaster that mixes same-season empirical draws with signed res

UnAC: Adaptive Visual Prompting with Abstraction and Stepwise Checking for Complex Multimodal Reasoning

arXiv:2605.03950v1 Announce Type: new Abstract: Although recent LMMs have become much stronger at visual perception, they remain unreliable on problems that require multi-step reasoning over visual ev

Local Ai

Uncertainty Estimation in Instance Segmentation of Affordances via Bayesian Visual Transformers

arXiv:2605.03614v1 Announce Type: new Abstract: Visual affordances identify regions in an image with potential interactions, offering a novel paradigm for scene understanding. Recognizing affordances

local-aiarxiv-cs-cv

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks

arXiv:2502.04419v3 Announce Type: replace-cross Abstract: Generating synthetic datasets via large language models (LLMs) has emerged as a promising approach to improve LLM performance. However, LLMs i

safetyarxiv-cs-cl

Unified Multimodal Visual Tracking with Dual Mixture-of-Experts

arXiv:2605.03716v1 Announce Type: new Abstract: Multimodal visual object tracking can be divided into to several kinds of tasks (e.g. RGB and RGB+X tracking), based on the input modality. Existing met

researcharxiv-cs-cv

Tutorials

Using Echo-State Networks to Reproduce Rare Events in Chaotic Systems

arXiv:2505.16208v2 Announce Type: replace-cross Abstract: We apply Echo-State Networks to predict time series and statistical properties of the competitive Lotka-Volterra model in the chaotic regime.

tutorialsarxiv-cs-lg

Using LLMs in Software Design: An Empirical Study of GitHub and A Practitioner Survey

arXiv:2605.01392v1 Announce Type: cross Abstract: Recent advancements in Large Language Models (LLMs) have demonstrated significant potential across a wide range of software engineering tasks, includi

researcharxiv-cs-ai

Vanishing L2 regularization for the softmax Multi Armed Bandit

arXiv:2605.03752v1 Announce Type: new Abstract: Multi Armed Bandit (MAB) algorithms are a cornerstone of reinforcement learning and have been studied both theoretically and numerically. One of the mos

When Alignment Isn't Enough: Response-Path Attacks on LLM Agents

arXiv:2605.02187v1 Announce Type: cross Abstract: Bring-Your-Own-Key (BYOK) agent architectures let users route LLM traffic through third-party relays, creating a critical integrity gap: a malicious r

A Closed-Form Persistence-Landmark Pipeline for Certified Point-Cloud and Graph Classification

arXiv:2605.02836v1 Announce Type: new Abstract: We introduce PLACE (Persistence-Landmark Analytic Classification Engine), a closed-form pipeline for classifying point clouds and graphs through their p

A decoupled diffusion planner that adapts to changing cost limits by using cost-conditioned generation for safety and reward gradients for performance

arXiv:2605.02777v1 Announce Type: new Abstract: Offline safe reinforcement learning often requires policies to adapt at deployment time to safety budgets that vary across episodes or change within a s

Applications

A Hybrid Approach for Closing the Sim2real Appearance Gap in Game Engine Synthetic Datasets

arXiv:2605.02291v1 Announce Type: new Abstract: Video game engines have been an important source for generating large volumes of visual synthetic datasets for training and evaluating computer vision a

applicationsarxiv-cs-cv

A hybrid solution approach for the Integrated Healthcare Timetabling Competition 2024

arXiv:2511.04685v2 Announce Type: replace Abstract: In this work, we present the solution approach for the Integrated Healthcare Timetabling Competition 2024 submitted by Team Twente, which ultimately

A Meta Reinforcement Learning Approach to Goals-Based Wealth Management

arXiv:2605.02300v1 Announce Type: new Abstract: Applying concepts related to zero-shot meta-learning and pre-training of foundation models, we develop a meta reinforcement learning approach (denoted M

researcharxiv-cs-lg

A Multimodal Dataset for Visually Grounded Ambiguity in Machine Translation

arXiv:2605.02035v1 Announce Type: new Abstract: Ambiguity resolution is a key challenge in multimodal machine translation (MMT), where models must genuinely leverage visual input to map an ambiguous e

A Parameter-Free First-Order Algorithm for Non-Convex Optimization with ilde{mkern1mu O}(epsilon^{-5/3}) Global Rate

arXiv:2605.02127v1 Announce Type: cross Abstract: We introduce PF-AGD, the first parameter-free, deterministic, accelerated first-order method to achieve O(epsilon^{-5/3}log(1/epsilon)) oracle complex

Accelerating battery research with an AI interface between FINALES and Kadi4Mat

arXiv:2605.00909v1 Announce Type: cross Abstract: The time-consuming formation process critically impacts the longevity of sodium-ion coin cells and End Of Life (EOL) performance. This study aims to o

Adaptive Estimation and Inference in Semi-parametric Heterogeneous Clustered Multitask Learning via Neyman Orthogonality

arXiv:2605.01907v1 Announce Type: cross Abstract: We study clustered multitask learning in a semiparametric setting where tasks share a latent cluster structure in their target parameters but exhibit

Agentic AI for Trip Planning Optimization Application

arXiv:2605.00276v1 Announce Type: new Abstract: Trip planning for intelligent vehicles increasingly requires selecting optimal routes rather than merely producing feasible itineraries, as interacting

An Efficient Metric for Data Quality Measurement in Imitation Learning

model-releasesarxiv-cs-ro

arXiv:2605.01544v1 Announce Type: new Abstract: Imitation learning (IL) has seen remarkable progress, yet field deployment of IL-powered robots remains hindered by the challenge of out-of-distribution

Anomaly-Preference Image Generation

arXiv:2605.02439v1 Announce Type: new Abstract: Synthesizing realistic and diverse anomalous samples from limited data is vital for robust model generalization. However, existing methods struggle to r

safetyarxiv-cs-cv

Artificial intelligence language technologies in multilingual healthcare: Grand challenges ahead

arXiv:2605.01441v1 Announce Type: new Abstract: AI language technologies (AILTs), increasingly enabled by large language models (LLMs), are becoming embedded in multilingual healthcare workflows for t

safetyarxiv-cs-cl

Agents

ATLAS: Adaptive Trading with LLM AgentS Through Dynamic Prompt Optimization and Multi-Agent Coordination

arXiv:2510.15949v4 Announce Type: replace-cross Abstract: Large language models show promise for financial decision-making, yet deploying them as autonomous trading agents raises fundamental challenge

agentsarxiv-cs-ai

Attention Sink Forges Native MoE in Attention Layers: Sink-Aware Training to Address Head Collapse

arXiv:2602.01203v2 Announce Type: replace Abstract: Large Language Models (LLMs) often assign disproportionate attention to the first token, a phenomenon known as the attention sink. Several recent ap

AttnRouter: Per-Category Attention Routing for Training-Free Image Editing on MMDiT

arXiv:2605.01480v1 Announce Type: new Abstract: We study training-free image editing on Qwen-Image-Edit-2511, a 60-block multi-modal diffusion transformer (MMDiT) that concatenates noise and source-im

Automatic Correction of Writing Anomalies in Hausa Texts

arXiv:2506.03820v2 Announce Type: replace Abstract: Hausa texts are often characterized by writing anomalies, such as incorrect character substitutions and spacing errors, which sometimes hinder natur

Autonomous Drift Learning in Data Streams: A Unified Perspective

arXiv:2605.01295v1 Announce Type: new Abstract: In the pursuit of autonomous learning systems, the foundational assumption of stationarity, the premise that data distributions and model behaviors rema

safetyarxiv-cs-lg

Autonomous Reliability Qualification of Ga_2O_3-based Hydrogen and Temperature Sensors via Safe Active Learning

arXiv:2605.00868v1 Announce Type: cross Abstract: We present a Safe Active Learning (SAL) framework for autonomous reliability characterization of rectifying Ga_2O_3-based devices under coupled therma

safetyarxiv-cs-lg

BadmintonGRF: A Multimodal Dataset and Benchmark for Markerless Ground Reaction Force Estimation in Badminton

arXiv:2605.01876v1 Announce Type: new Abstract: Multimodal resources for non-periodic court sports with laboratory-grade sensing remain scarce: few publicly pair instrumented ground reaction force (GR

BadSNN: Backdoor Attacks on Spiking Neural Networks via Adversarial Spiking Neuron

arXiv:2602.07200v2 Announce Type: replace-cross Abstract: Spiking Neural Networks (SNNs) are energy-efficient counterparts of Deep Neural Networks (DNNs) with high biological plausibility, as informat

researcharxiv-cs-ai

Beating the Style Detector: Three Hours of Agentic Research on the AI-Text Arms Race

model-releasesarxiv-cs-cl

arXiv:2605.02620v1 Announce Type: new Abstract: Reproducing an empirical NLP study used to take weeks. Given the released data and a modern agentic-research harness, we redo every experiment of a rece

Benchmarking LightGBM and BiLSTM for Sentiment Analysis on Indonesian E-Commerce Reviews

arXiv:2605.01322v1 Announce Type: new Abstract: This study presents a comparative analysis between two primary approaches in Natural Language Processing (NLP): Machine Learning (ML) utilizing the PyCa

Boundary Mass and the Soft-to-Hard Limit in Mixture-of-Experts

arXiv:2605.02124v1 Announce Type: new Abstract: Softmax-routed mixture-of-experts models approach hard routing as the temperature tends to zero, but this limit is singular near routing ties. This pape

researcharxiv-cs-lg

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments

arXiv:2508.19932v2 Announce Type: replace Abstract: The proliferation of digital payment platforms has transformed commerce, offering unmatched convenience and accessibility globally. However, this gr

Causal Foundations of Collective Agency

arXiv:2605.00248v1 Announce Type: new Abstract: A key challenge for the safety of advanced AI systems is the possibility that multiple simpler agents might inadvertently form a collective agent with c

safetyarxiv-cs-ai

CGFformer: Cluster-Guidance Frequency Transformer for Pansharpening

arXiv:2605.01490v1 Announce Type: new Abstract: Pansharpening aims to generate high-resolution multispectral (HRMS) images by fusing low-resolution multispectral (LRMS) images with high-resolution pan

Chebyshev-Augmented One-Shot Transfer Learning for PINNs on Nonlinear Differential Equations

arXiv:2605.01634v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) offer a flexible paradigm for solving differential equations by embedding governing laws into the training obje

CoFrGeNet: Continued Fraction Architectures for Language Generation

arXiv:2601.21766v3 Announce Type: replace Abstract: Transformers are arguably the preferred architecture for language generation. In this paper, inspired by continued fractions, we introduce a new fun

Contrastive Residual Energy Test-time Adaptation

arXiv:2505.19607v2 Announce Type: replace Abstract: Test-time adaptation (TTA) enhances model robustness by enabling adaptation to target distributions that differ from training distributions, improvi

safetyarxiv-cs-lg

Coopetition-Gym v1: A Formally Grounded Platform for Mixed-Motive Multi-Agent Reinforcement Learning under Strategic Coopetition

arXiv:2605.02063v1 Announce Type: cross Abstract: We present Coopetition-Gym v1, a benchmark platform for mixed-motive multi-agent reinforcement learning under strategic coopetition. The platform comp

Hardware

DELTA: Dynamic Layer-Aware Token Attention for Efficient Long-Context Reasoning

arXiv:2510.09883v2 Announce Type: replace Abstract: Large reasoning models (LRMs) achieve state-of-the-art performance on challenging benchmarks by generating long chains of intermediate steps, but th

hardwarearxiv-cs-cl

Dependency Parsing Across the Resource Spectrum: Evaluating Architectures on High and Low-Resource Languages

arXiv:2605.02608v1 Announce Type: new Abstract: Transformer-based models achieve state-of-the-art dependency parsing for high-resource languages, yet their advantage over simpler architectures in low-

Differentiable Multiphysics Co-Optimization via Implicit Neural Representations: A Transient Hamburger-Cooking Benchmark

arXiv:2605.01040v1 Announce Type: cross Abstract: The co-optimization of geometry and physical parameters remains challenging in transient multiphysics systems involving moving boundaries, nonlinear m

Applications

DIPLI: Deep Image Prior Lucky Imaging for Blind Astronomical Image Restoration

arXiv:2503.15984v3 Announce Type: replace Abstract: Modern image restoration and super-resolution methods utilize deep learning due to its superior performance compared to traditional algorithms. Howe

applicationsarxiv-cs-cv

DuFal: Dual-Frequency-Aware Learning for High-Fidelity Extremely Sparse-view CBCT Reconstruction

arXiv:2601.15416v2 Announce Type: replace Abstract: Sparse-view Cone-Beam Computed Tomography reconstruction from limited X-ray projections remains a challenging problem in medical imaging due to the

EditPropBench: Measuring Factual Edit Propagation in Scientific Manuscripts

model-releasesarxiv-cs-cl

arXiv:2605.02083v1 Announce Type: new Abstract: Local factual edits in scientific manuscripts often create non-local revision obligations. If a dataset changes from 215 to 80 documents, claims such as