Search: “models”

LLMs Can't Play Hangman: On the Necessity of a Private Working Memory for Language Agents

arXiv:2601.06973v2 Announce Type: replace Abstract: As LLMs move from text completion toward autonomous agents, they remain constrained by the standard chat interface, which lacks private working memo

agentsarxiv-cs-cl

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Local Ai

LLMs Interpret, Embeddings Organize, Graphs Emerge: Agent-Driven Compilation of Scientific Knowledge

DGX agent

arXiv:2608.29612v1 Announce Type: new Abstract: Sustained scientific work requires a knowledge substrate that carries interpretation across tasks and preserves paths to source evidence. We call this p

local-aiarxiv-cs-ai

1 Sept 2026

MA-RAG: Multi-Agent Retrieval-Augmented Generation for Query-Driven Summarization of Longitudinal Parkinson's Disease Assessments

arXiv:2608.28624v1 Announce Type: cross Abstract: Accurate interpretation of single-visit and longitudinal clinical assessments for Parkinson's disease is time-consuming and often depends on specialis

Measuring Similarity between Artistic and AI Generated Images using Siamese Neural Networks

arXiv:2608.28671v1 Announce Type: cross Abstract: AI-generated art has sparked debates around potential plagiarism, as these images may closely resemble existing artworks. This research quantifies the

MedAgent-R1: Faithfulness-Aware Reinforcement Learning for Evidence-Grounded Medical Reasoning

arXiv:2608.30676v1 Announce Type: new Abstract: When medical AI systems hallucinate clinical reasoning, the consequences extend beyond incorrect answers: fabricated justifications that superficially r

safetyarxiv-cs-ai

MEGA: Message Passing Neural Networks for Multigraphs with EdGe Attributes

arXiv:2412.00241v3 Announce Type: replace Abstract: Edge-attributed multigraphs, in which multiple edges with distinct attributes connect the same pair of nodes, arise naturally in many real-world sys

applicationsarxiv-cs-lg

Tutorials

MEOM: Multi-View Expected-OKS Maximization for Human Pose Triangulation

arXiv:2608.30521v1 Announce Type: new Abstract: Conventional algebraic triangulation solves 3D human pose estimation (HPE) from multi-view 2D keypoints. The typical approach, decoding 2D keypoints fro

tutorialsarxiv-cs-cv

Multi-Marginal Flow Matching with Adversarially Learnt Interpolants

arXiv:2510.01159v3 Announce Type: replace Abstract: Learning the dynamics of a process given sampled observations at several time points is an important but difficult task in many scientific applicati

Multi-Sensor Mapping of Vulnerable Urban Settlements Using SAR, Multispectral, and Hyperspectral Imagery: A Case Study in Cordoba, Argentina

arXiv:2608.28680v1 Announce Type: new Abstract: Informal settlements represent a major urban challenge in rapidly expanding cities, yet their identification from Earth Observation (EO) data remains di

applicationsarxiv-cs-cv

Multi-View Reflective Surface Inspection via Semantic-Saliency Cross-Verification

arXiv:2608.30997v1 Announce Type: new Abstract: Reflective smartphone cover glass is challenging to inspect from a single fixed viewpoint because defect visibility varies with viewing geometry and spe

applicationsarxiv-cs-cv

NBS: No Bias Stereo

arXiv:2608.28933v1 Announce Type: new Abstract: Stereo reconstruction is one of the last remaining Computer Vision tasks where all state-of-the-art methods employ a heavy architectural inductive bias.

safetyarxiv-cs-cv

Hardware

NepScript Genesis: Neural Architecture Search for Handwritten Devanagari Digit Synthesis

arXiv:2608.29540v1 Announce Type: new Abstract: This paper introduces NepScript Genesis, a Neural Architecture Search (NAS) framework for automated Generative Adversarial Network (GAN) discovery, appl

hardwarearxiv-cs-cv

Neural 3D Object Reconstruction with Small-Scale Unmanned Aerial Vehicles

arXiv:2509.12458v3 Announce Type: replace-cross Abstract: Miniaturized Uncrewed Aerial Vehicles (UAVs) can access indoor and hard-to-reach spaces, but severe constraints on payload and autonomy have l

agentsarxiv-cs-cv

Not All or None: Dynamic Construction of Target-aware Memory Graph for Conversational Stance Detection

arXiv:2608.29066v1 Announce Type: cross Abstract: Stance detection is crucial for understanding the underlying attitude of an expression towards a target. Conversational stance detection is a more cha

applicationsarxiv-cs-ai

Hardware

NVIDIA and CrowdStrike Strengthen Agentic Cybersecurity Frontier

“We’re at an inflection point in cybersecurity,” Jensen Huang told a sold-out crowd at CrowdStrike’s Fal.Con 2026 in Las Vegas Tuesday. Attacks are now automated. Defense has to be, too. The NVIDIA fo

hardwarenvidia-blog

Oculi: A Conversational Agentic Platform for Automated Credit Risk Analysis

arXiv:2608.28944v1 Announce Type: new Abstract: Credit risk analysis in financial institutions traditionally requires analysts to manually write SQL queries, run statistical computations, and build vi

On the Instance Hardness as a Decision Criterion in TinyML Systems

arXiv:2608.29913v1 Announce Type: new Abstract: TinyML includes the implementation of machine learning on devices with limited memory and computing resources. With the development of technology, AI sy

On the Optimality of Kinship Naming: an Information-theoretic Approach

arXiv:2511.19120v2 Announce Type: replace-cross Abstract: The structure of naming systems in natural languages hinges on a trade-off between high informativeness and low complexity. Focusing on the do

On the Role of MRI Sequences in Cross-Dataset Generalization for Brain Tumor Segmentation

arXiv:2608.29944v1 Announce Type: new Abstract: Brain tumor segmentation in magnetic resonance imaging (MRI) is a critical task for diagnosis and treatment planning. Despite the success of deep learni

ORDDAR: Observation-Driven Reasoning for Distortion-Resilient Decision, Action, and Cognitive Recovery

arXiv:2608.28704v1 Announce Type: new Abstract: AI agents increasingly perform long-term reasoning, planning, tool use, memory integration, and autonomous decision making, yet erroneous intermediate s

Overreliance on AI in Information-seeking from Video Content

arXiv:2603.19843v2 Announce Type: replace-cross Abstract: The ubiquity of multimedia content is reshaping online information spaces, particularly in social media environments. At the same time, search

safetyarxiv-cs-cl

PAC: Progress-Augmented Advantage Curriculum for Multi-Task Reinforcement Learning of LLMs

arXiv:2608.30528v1 Announce Type: new Abstract: Reinforcement learning (RL) is used to improve the reasoning abilities of LLMs, while training data span heterogeneous tasks. However, most RL post-trai

safetyarxiv-cs-lg

Parallel Time-Band Mixing with Learned Observation-Adding for Robust ASR Front-Ends

arXiv:2608.30326v1 Announce Type: cross Abstract: Speech enhancement is often used as a front-end for robust ASR, yet recurrent temporal and cross-band modules introduce sequential dependencies that r

PathBridger: Subgoal Bridges for Offline Goal-Conditioned Reinforcement Learning

arXiv:2608.29061v1 Announce Type: new Abstract: Offline goal-conditioned reinforcement learning (GCRL) aims to learn policies for reaching diverse goals entirely from fixed trajectory data. Long-horiz

safetyarxiv-cs-lg

Perforated Backpropagation: A Neuroscience Inspired Extension to Artificial Neural Networks

arXiv:2501.18018v2 Announce Type: replace-cross Abstract: The neurons of artificial neural networks were originally invented when much less was known about biological neurons than is known today. Our

Personalized Treatment Outcome Prediction from Scarce Data via Dual-Channel Knowledge Distillation and Adaptive Fusion

arXiv:2510.26444v2 Announce Type: replace-cross Abstract: Personalized treatment outcome prediction based on trial data for small-sample and rare patient groups is a critical task in precision medicin

Tutorials

Predicting the Unpredictable: LLM-powered Long-term Chaotic Time Series Forecasting under Short-term Observations

arXiv:2608.29579v1 Announce Type: new Abstract: Chaotic time series forecasting is a challenging task due to its sensitivity to initial conditions and long-term unpredictability. Traditional methods t

tutorialsarxiv-cs-lg

Prediction-Powered Conditional Inference

arXiv:2603.05575v2 Announce Type: replace-cross Abstract: We study prediction-powered conditional inference in the setting where labeled data are scarce, unlabeled covariates are abundant, and a black

Privacy-Preserving Generation of Clinical Narratives from Medical Terminologies

arXiv:2509.10882v2 Announce Type: replace Abstract: In high-stakes domains such as healthcare, privacy concerns severely limit the use of real-world training data. Differentially private (DP) syntheti

applicationsarxiv-cs-cl

ProGS: Towards Progressive Coding for 3D Gaussian Splatting

arXiv:2603.09703v2 Announce Type: replace Abstract: Progressive transmission of 3D Gaussian Splatting (3DGS) requires each completed transmission stage to be decodable from received data and directly

Proximity3D: Shape from Capacitive Proximity on Sensing Manifold

arXiv:2608.30344v1 Announce Type: new Abstract: Most shape reconstruction methods assume measurements defined over planar sensing domains, such as RGB images or depth maps. In this paper, we use a cur

Quantitative Evidence Mining for Plausibility-Aware Biomedical AI

arXiv:2608.30393v1 Announce Type: new Abstract: Biomedical artificial intelligence (AI) systems increasingly extract, organize, and reuse scientific claims from literature, clinical trials, and regula

agentsarxiv-cs-cl

RailGen: Improving Railway Intrusion Detection via Agent-Guided Small-Scale Foreign Object Generation

arXiv:2608.30727v1 Announce Type: cross Abstract: Small-object detection under long-tailed data distributions is a fundamental yet challenging problem in multimedia. Railway Foreign Object Detection (

safetyarxiv-cs-ai

RailSyn: Diagnosis-Guided Image Generation for Traceable Data Completion in Railway Foreign Object Detection

arXiv:2608.30709v1 Announce Type: cross Abstract: Railway foreign object detection (RFOD) is critical to safe railway operation, yet scarce real positive samples incompletely represent task-relevant v

RankShift: In-Database Detection and Explanation of Categorical Shifts

arXiv:2608.28922v1 Announce Type: new Abstract: A login service can receive its usual number of failed sign-ins while one source grows from 2% to 30% of them. The same pattern appears in system logs w

Reverse N-Wise Output-Oriented Testing for AI/ML and Quantum Computing Systems

arXiv:2602.14275v2 Announce Type: replace-cross Abstract: Artificial intelligence/machine learning (AI/ML) systems and emerging quantum computing software present unprecedented testing challenges char

safetyarxiv-cs-ai

RL-FAT: Reinforcement Learning for Fair Adversarial Training

arXiv:2608.29247v1 Announce Type: new Abstract: Deep neural networks remain highly vulnerable to adversarial perturbations, and adversarial training (AT) has become a widely used approach for improvin

safetyarxiv-cs-lg

RLinf-USER: A Unified and Extensible System for Real-World Online Policy Learning in Embodied AI

arXiv:2602.07837v4 Announce Type: replace Abstract: Online policy learning directly in the physical world is a promising yet challenging direction for embodied intelligence. Unlike simulation, real-wo

safetyarxiv-cs-ro

Robust retinal biometrics for patient identity verification and retrieval across age and imaging devices

arXiv:2608.31094v1 Announce Type: new Abstract: Patient identity errors can compromise longitudinal medical records, research databases, and downstream clinical decisions. We present a retinal biometr

Local Ai

ScaffoldAgent: Utility-Guided Dynamic Outline Optimization for Open-Ended Deep Research

arXiv:2606.20122v2 Announce Type: replace Abstract: Open-ended deep research (OEDR) requires systems to acquire knowledge through multi-round retrieval and generate coherent long-form reports. The out

local-aiarxiv-cs-ai

See the Change, Keep the Flow: Unsupervised Action Segmentation via Spectral-Temporal Representation Learning

arXiv:2608.29611v1 Announce Type: new Abstract: Unsupervised action segmentation aims to discover latent action categories and their temporal organization without action annotations. Optimal transport

SELECT: SELEctive Context Transfer for Class-Incremental Semantic Segmentation

arXiv:2608.30281v1 Announce Type: new Abstract: Class-Incremental Semantic Segmentation (CISS) is fundamentally challenged by catastrophic forgetting and background shift, where learning new concepts

Separable Nonnegative Matrix Factorization Using Powered Ratio-of-Norms Regularization

arXiv:2608.28799v1 Announce Type: cross Abstract: Separable nonnegative matrix factorization (SNMF) has been widely used for low-rank representation and clustering of nonnegative data, owing to its ab

Simulation-Based Evaluation of Energy-Constrained Quantum-Classical Competition

arXiv:2308.08025v2 Announce Type: replace-cross Abstract: This paper develops a simulation-based framework for evaluating the energy implications of quantum and classical computing firms competing in

Sketch2Inspire: Structure-Sensitive Evaluation for Product Retrieval

arXiv:2608.29364v1 Announce Type: new Abstract: Early-stage product design retrieval often requires more than category recognition: designers may need reference examples that match both a short semant

Sources: AfterQuery, which sells coding and finance training data to AI labs, has hit a valuation of 3.2B, up from 300M in April, and is profitable (Anna Tong/Forbes)

Anna Tong / Forbes: Sources: AfterQuery, which sells coding and finance training data to AI labs, has hit a valuation of 3.2B, up from 300M in April, and is profitable — Twenty three year-old Spencer

applicationstechmeme

Spectral Analysis for Sparse Matrix Computation: Insights and Potential

arXiv:2608.29362v1 Announce Type: cross Abstract: Sparse computations are fundamental to scientific computing, graph analytics, and machine learning, yet their performance is highly sensitive to the d

Local Ai

STAGEET: Stage-wise Typed Edit Tagging for Grammatical Error Correction with Arabic as a Case Study

arXiv:2608.28614v1 Announce Type: cross Abstract: Sequence-to-edit approaches make grammatical error correction (GEC) efficient and locally interpretable by predicting edit labels over the input rathe

local-aiarxiv-cs-ai