Search: “research”

Learnable Motion-Focused Tokenization for Effective and Efficient Video Unsupervised Domain Adaptation

arXiv:2604.09955v1 Announce Type: new Abstract: Video Unsupervised Domain Adaptation (VUDA) poses a significant challenge in action recognition, requiring the adaptation of a model from a labeled sour

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

LIFT: A Novel Framework for Enhancing Long-Context Understanding of LLMs via Long Input Fine-Tuning

DGX agent

arXiv:2502.14644v5 Announce Type: replace Abstract: Long context understanding remains challenging for large language models due to their limited context windows. This paper introduces Long Input Fine

model-releasesarxiv-cs-cl

14 Apr 2026

LiveCLKTBench: Towards Reliable Evaluation of Cross-Lingual Knowledge Transfer in Multilingual LLMs

arXiv:2511.14774v3 Announce Type: replace-cross Abstract: Evaluating cross-lingual knowledge transfer in large language models is challenging, as correct answers in a target language may arise either

Machine Learning-Based Detection of MCP Attacks

arXiv:2604.10534v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) is a new and emerging technology that extends the functionality of large language models, improving workflows but als

agentsarxiv-cs-ai

Masked Training for Robust Arrhythmia Detection from Digitalized Multiple Layout ECG Images

arXiv:2508.09165v3 Announce Type: replace-cross Abstract: Background: Electrocardiograms are indispensable for diagnosing cardiovascular diseases, yet in many settings they exist only as paper printou

METER: Evaluating Multi-Level Contextual Causal Reasoning in Large Language Models

arXiv:2604.11502v1 Announce Type: cross Abstract: Contextual causal reasoning is a critical yet challenging capability for Large Language Models (LLMs). Existing benchmarks, however, often evaluate th

MMR-AD: A Large-Scale Multimodal Dataset for Benchmarking General Anomaly Detection with Multimodal Large Language Models

arXiv:2604.10971v1 Announce Type: cross Abstract: In the progress of industrial anomaly detection, general anomaly detection (GAD) is an emerging trend and also the ultimate goal. Unlike the conventio

MR-Coupler: Automated Metamorphic Test Generation via Functional Coupling Analysis

arXiv:2604.10126v1 Announce Type: cross Abstract: Metamorphic testing (MT) is a widely recognized technique for alleviating the oracle problem in software testing. However, its adoption is hindered by

Multi-Head Attention based interaction-aware architecture for Bangla Handwritten Character Recognition: Introducing a Primary Dataset

model-releasesarxiv-cs-cv

arXiv:2604.09717v1 Announce Type: new Abstract: Character recognition is the fundamental part of an optical character recognition (OCR) system. Word recognition, sentence transcription, document digit

Multi-Model Synthetic Training for Mission-Critical Small Language Models

arXiv:2509.13047v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities across many domains, yet their application to specialized fields remain

NameBERT: Scaling Name-Based Nationality Classification with LLM-Augmented Open Academic Data

arXiv:2604.10401v1 Announce Type: new Abstract: Inferring nationality from personal names is a critical capability for equity and bias monitoring, personalization, and a valuable tool in biomedical an

safetyarxiv-cs-cl

Nationality encoding in language model hidden states: Probing culturally differentiated representations in persona-conditioned academic text

arXiv:2604.10151v1 Announce Type: new Abstract: Large language models are increasingly used as writing tools and pedagogical resources in English for Academic Purposes, but it remains unclear whether

Normative Common Ground Replication (NormCoRe): Replication-by-Translation for Studying Norms in Multi-Agent AI

arXiv:2603.11974v2 Announce Type: replace Abstract: In the late 2010s, the fashion trend NormCore framed sameness as a signal of belonging, illustrating how norms emerge through collective coordinatio

NovBench: Evaluating Large Language Models on Academic Paper Novelty Assessment

arXiv:2604.11543v1 Announce Type: cross Abstract: Novelty is a core requirement in academic publishing and a central focus of peer review, yet the growing volume of submissions has placed increasing p

NTIRE 2026 Challenge on Robust AI-Generated Image Detection in the Wild

arXiv:2604.11487v1 Announce Type: new Abstract: This paper presents an overview of the NTIRE 2026 Challenge on Robust AI-Generated Image Detection in the Wild, held in conjunction with the NTIRE works

NTIRE 2026 Challenge on Single Image Reflection Removal in the Wild: Datasets, Results, and Methods

arXiv:2604.10321v1 Announce Type: new Abstract: In this paper, we review the NTIRE 2026 challenge on single-image reflection removal (SIRR) in the Wild. SIRR is a fundamental task in image restoration

Hardware

Nvidia unveils Ising AI models for quantum error correction and calibration

Technology and computing giant Nvidia Corp. today announced the release of Ising, the world’s first open artificial intelligence model family aimed at quantum computing calibration and error correctio

hardwaresiliconangle

ODUTQA-MDC: A Task for Open-Domain Underspecified Tabular QA with Multi-turn Dialogue-based Clarification

arXiv:2604.10159v1 Announce Type: new Abstract: The advancement of large language models (LLMs) has enhanced tabular question answering (Tabular QA), yet they struggle with open-domain queries exhibit

Online Reasoning Video Object Segmentation

model-releasesarxiv-cs-cv

arXiv:2604.11411v1 Announce Type: new Abstract: Reasoning video object segmentation predicts pixel-level masks in videos from natural-language queries that may involve implicit and temporally grounded

Orthogonal machine learning for conditional odds and risk ratios

arXiv:2604.10412v1 Announce Type: cross Abstract: Conditional effects are commonly used measures for understanding how treatment effects vary across different groups, and are often used to target trea

safetyarxiv-cs-lg

Our technical report, including how we designed the reward and the performance/latency Pareto frontier, is live here: https://cognition.ai/b…

Cognition AI has published a technical report detailing the design methodology behind their reward system, likely related to their Devin AI software engineering agent. The report covers the performanc

agentscognition-ai--x

PAT: Privacy-Preserving Adversarial Transfer for Accurate, Robust and Privacy-Preserving EEG Decoding

arXiv:2412.11390v3 Announce Type: replace-cross Abstract: An electroencephalogram (EEG)-based brain-computer interface (BCI) enables direct communication between the brain and external devices. Howeve

safetyarxiv-cs-lg

Perceived Importance of Cognitive Skills Among Computing Students in the Era of AI

arXiv:2604.10730v1 Announce Type: cross Abstract: The availability and increasing integration of generative AI tools have transformed computing education. While AI in education presents opportunities,

applicationsarxiv-cs-ai

Perception-aware Exploration for Consumer-grade UAVs

arXiv:2511.14393v2 Announce Type: replace Abstract: In our work, we extend the current state-of-the-art approach for autonomous multi-UAV exploration to consumer-level UAVs, such as the DJI Mini 3 Pro

agentsarxiv-cs-ro

Physics-Informed State Space Models for Reliable Solar Irradiance Forecasting in Off-Grid Systems

arXiv:2604.11807v1 Announce Type: cross Abstract: The stable operation of autonomous off-grid photovoltaic systems dictates reliance on solar forecasting algorithms that respect atmospheric thermodyna

agentsarxiv-cs-ai

Policy-Guided Threat Hunting: An LLM enabled Framework with Splunk SOC Triage

arXiv:2603.23966v3 Announce Type: replace-cross Abstract: With frequently evolving Advanced Persistent Threats (APTs) in cyberspace, traditional security solutions approaches have become inadequate fo

Polyglot Teachers: Evaluating Language Models for Multilingual Synthetic Data Generation

arXiv:2604.11290v1 Announce Type: new Abstract: Synthesizing supervised finetuning (SFT) data from language models (LMs) to teach smaller models multilingual tasks has become increasingly common. Howe

Post-Processing Methods for Improving Accuracy in MRI Inpainting

arXiv:2510.15282v2 Announce Type: replace-cross Abstract: Magnetic Resonance Imaging (MRI) is the primary imaging modality used in the diagnosis, assessment, and treatment planning for brain pathologi

local-aiarxiv-cs-ai

PosterGen: Aesthetic-Aware Multi-Modal Paper-to-Poster Generation via Multi-Agent LLMs

arXiv:2508.17188v2 Announce Type: replace Abstract: Multi-agent systems built upon large language models (LLMs) have demonstrated remarkable capabilities in tackling complex compositional tasks. In th

agentsarxiv-cs-ai

Quantization Robustness to Input Degradations for Object Detection

arXiv:2508.19600v2 Announce Type: replace Abstract: Post-training quantization (PTQ) is crucial for deploying efficient object detection models, like YOLO, on resource-constrained devices. However, th

Reasoning as Gradient: Scaling MLE Agents Beyond Tree Search

arXiv:2603.01692v3 Announce Type: replace-cross Abstract: LLM-based agents for machine learning engineering (MLE) predominantly rely on tree search, a form of gradient-free optimization that uses scal

Resisting Humanization: Ethical Front-End Design Choices in AI for Sensitive Contexts

arXiv:2603.24853v2 Announce Type: replace Abstract: Ethical debates in AI have primarily focused on back-end issues such as data governance, model training, and algorithmic decision-making. Less atten

applicationsarxiv-cs-ai

Risk Awareness Injection: Calibrating Vision-Language Models for Safety without Compromising Utility

arXiv:2602.03402v3 Announce Type: replace Abstract: Vision language models (VLMs) extend the reasoning capabilities of large language models (LLMs) to cross-modal settings, yet remain highly vulnerabl

RPA-Check: A Multi-Stage Automated Framework for Evaluating Dynamic LLM-based Role-Playing Agents

arXiv:2604.11655v1 Announce Type: cross Abstract: The rapid adoption of Large Language Models (LLMs) in interactive systems has enabled the creation of dynamic, open-ended Role-Playing Agents (RPAs).

local-aiarxiv-cs-ai

Saar-Voice: A Multi-Speaker Saarbrucken Dialect Speech Corpus

arXiv:2604.11803v1 Announce Type: new Abstract: Natural language processing (NLP) and speech technologies have made significant progress in recent years; however, they remain largely focused on standa

local-aiarxiv-cs-cl

Scaling unstructured enterprise knowledge with BigQuery Graph, and Kineviz GraphXR

model-releasesgoogle-cloud-ai

Over 80% of enterprise data lives in unstructured form — PDFs, emails, reports, regulatory filings. Most of the time, such sources contain critical business information, yet they remain difficult to a

SciPredict: Can LLMs Predict the Outcomes of Scientific Experiments in Natural Sciences?

arXiv:2604.10718v1 Announce Type: new Abstract: Accelerating scientific discovery requires the identification of which experiments would yield the best outcomes before committing resources to costly p

SemaClaw: A Step Towards General-Purpose Personal AI Agents through Harness Engineering

arXiv:2604.11548v1 Announce Type: new Abstract: The rise of OpenClaw in early 2026 marks the moment when millions of users began deploying personal AI agents into their daily lives, delegating tasks r

Simulating Organized Group Behavior: New Framework, Benchmark, and Analysis

arXiv:2604.09874v1 Announce Type: new Abstract: Simulating how organized groups (e.g., corporations) make decisions (e.g., responding to a competitor's move) is essential for understanding real-world

SpatialScore: Towards Comprehensive Evaluation for Spatial Intelligence

arXiv:2505.17012v3 Announce Type: replace-cross Abstract: Existing evaluations of multimodal large language models (MLLMs) on spatial intelligence are typically fragmented and limited in scope. In thi

SRBench: A Comprehensive Benchmark for Sequential Recommendation with Large Language Models

arXiv:2604.09553v1 Announce Type: cross Abstract: LLM development has aroused great interest in Sequential Recommendation (SR) applications. However, comprehensive evaluation of SR models remains lack

StarVLA-alpha: Reducing Complexity in Vision-Language-Action Systems

arXiv:2604.11757v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for building general-purpose robotic agents. However, the VLA landsc

Steered LLM Activations are Non-Surjective

arXiv:2604.09839v1 Announce Type: new Abstract: Activation steering is a popular white-box control technique that modifies model activations to elicit an abstract change in output behavior. It has als

The Blind Spot of Agent Safety: How Benign User Instructions Expose Critical Vulnerabilities in Computer-Use Agents

arXiv:2604.10577v1 Announce Type: cross Abstract: Computer-use agents (CUAs) can now autonomously complete complex tasks in real digital environments, but when misled, they can also be used to automat

The @MiniMax_AI team is receptive to community feedback and are updating the license. See the latest here. https://x.com/RyanLeeMiniMax/stat…

The @MiniMax_AI team is receptive to community feedback and are updating the license. See the latest here. https://x.com/RyanLeeMiniMax/status/2044132777877221515?s=20 I just updated our license. For

local-ailm-studio--x

The Paradox of Professional Input: How Expert Collaboration with AI Systems Shapes Their Future Value

arXiv:2504.12654v1 Announce Type: cross Abstract: This perspective paper examines a fundamental paradox in the relationship between professional expertise and artificial intelligence: as domain expert

Tutorials

The second technique was two-phase post-training. We first trained purely for capability, then added a latency penalty calibrated from real …

The second technique was two-phase post-training. We first trained purely for capability, then added a latency penalty calibrated from real dogfooding data based on the CDF of how long users stay on S

tutorialscognition-ai--x

There are multiple realities of AI right now. And what you have access to drastically changes your workflows, trust in AI, and ability to ad…

model-releasesallie-k--miller--x

There are multiple realities of AI right now. And what you have access to drastically changes your workflows, trust in AI, and ability to adapt to the future. Here’s the briefest state of the AI world