Search: “models”

GRIN+: Towards Fast Yet Effective Machine Unlearning for Imbalanced Medical Data

arXiv:2609.15571v1 Announce Type: new Abstract: As deep learning models become fundamental to modern healthcare, the 'Right to be Forgotten' mandated by privacy regulations like GDPR and HIPAA necessi

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Inside VLM Chart Reading: Tracing Value Reading from Vertical Bar Charts Across Space and Depth

DGX agent

arXiv:2609.13745v1 Announce Type: new Abstract: Vision--language models (VLMs) can answer chart questions accurately, but output accuracy does not show how they combine the evidence needed to recover

model-releasesarxiv-cs-cl

15 Sept 2026

Learning Through Energy Refinement and Manifold Projection: A Cooperative EBM-AE Framework

arXiv:2609.13917v1 Announce Type: new Abstract: Energy-Based Models (EBMs) provide a flexible framework for generative modeling by learning an energy landscape that assigns low energy values to realis

researcharxiv-cs-lg

LLM-Based Schema-Aware Split Learning for Privacy-Preserving Mental Distress Prediction Across Heterogeneous Surveys

arXiv:2609.15871v1 Announce Type: cross Abstract: Rising societal and lifestyle complexity has been linked to a growing prevalence of mental distress worldwide. Educational institutions, workplaces, c

Agents

MedSAM3: Delving into Segment Anything with Medical Concepts

arXiv:2511.19046v2 Announce Type: replace-cross Abstract: Medical image segmentation is fundamental for biomedical discovery. Existing methods lack generalizability and demand extensive, time-consumin

agentsarxiv-cs-ai

MemRiskBench: Trace-Aware Risk-Preserving Evaluation for Long-Horizon LLM Agents

arXiv:2609.14976v1 Announce Type: new Abstract: Long-horizon LLM agents accumulate memory across sessions, creating sparse but high-impact risks: stale facts, conflicting updates, cross-user leakage,

Not all Negation Cues are Equal: Affixal Negations Yield Better Negation Understanding

arXiv:2609.13685v1 Announce Type: cross Abstract: Negation remains a longstanding challenge for both language models (LMs) and large language models (LLMs). Prior work mainly focuses on a small set of

researcharxiv-cs-ai

‘Now We Can Know Everything and Do Anything,’ Jensen Huang Says at Dreamforce

model-releasesnvidia-blog

Know everything. Do anything. That was the message NVIDIA founder and CEO Jensen Huang brought to Salesforce Dreamforce Tuesday, joining CEO Marc Benioff onstage in an appearance that coincided with t

Odds-Shift Slippage in One-vs-Rest Rankers: Diagnosing and Repairing Reweighting-Induced Top-K Errors

arXiv:2609.13810v1 Announce Type: cross Abstract: One-vs-rest rankers that show each user the top-K of many rare labels usually counter imbalance with a per-label positive-class weight, scale_pos_weig

Open-UniMo: Towards Unified Motion-Language Understanding and Generation in the Open World

arXiv:2609.14615v1 Announce Type: cross Abstract: Unified motion generation and understanding is crucial for embodied AI systems that can both synthesize and interpret human actions in open-world envi

Safety

PolicyMem: Geometric Policy Memory for LLM Governance

arXiv:2609.13734v1 Announce Type: cross Abstract: As large language models (LLMs) are increasingly deployed in real-world high-stakes applications, effective governance has become essential. Existing

safetyarxiv-cs-ai

Pretraining for Sample-Efficient Neural Interfaces

arXiv:2609.13507v1 Announce Type: new Abstract: Brain-computer interfaces (BCIs) decode neural activity to restore lost function. Typically, training a high-performance neural decoder requires a large

Quantum-Gated LiteSSD: A Parameter-Efficient Lightweight Hybrid Quantum-Classical Framework for Forward-Looking Sonar Object Detection

arXiv:2609.14025v1 Announce Type: new Abstract: Forward-looking sonar object detection is essential for underwater perception, yet deployment on embedded platforms requires highly compact models. To a

Tutorials

Rethinking the Implications of Human Feedback for Preference Learning in Human-Robot Collaboration

arXiv:2609.13982v1 Announce Type: cross Abstract: In Human-Robot Interaction, the standard approach to learn a reward model that represents human preferences for robot behavior consists of three steps

tutorialsarxiv-cs-ai

Root-Cause Attribution Is a Search Problem: Continual Search for Long-Horizon Agent Failures

arXiv:2609.13463v1 Announce Type: new Abstract: The increasing deployment of AI agents in long-horizon tasks yields massive execution logs. Diagnosing failures within these records is crucial for reli

SALUTE: Benchmarking and Adapting LLMs for the Defense Domain

arXiv:2609.15022v1 Announce Type: new Abstract: Defense is a knowledge-intensive domain that requires precise understanding of specialized terminology, doctrinal concepts, operational procedures, and

Sanity Checking Causal Representation Learning on a Simple Real-World System

arXiv:2502.20099v3 Announce Type: replace-cross Abstract: We evaluate methods for causal representation learning (CRL) on a simple, real-world system that satisfies the basic problem setup of CRL. The

Tutorials

SeqMaestro: From nucleotide sequences to biological hypotheses through interpretable machine learning

arXiv:2609.14882v1 Announce Type: cross Abstract: Nucleotide sequence analysis is central to problems spanning regulatory genomics, evolutionary biology, and phenotype prediction. Classical bioinforma

tutorialsarxiv-cs-ai

SpermYOLO: A Coordinated YOLO-Based Detector for Accurate and Efficient Sperm and Impurity Detection in Microscopic Images

arXiv:2609.14278v1 Announce Type: cross Abstract: Accurate sperm detection is essential for computer-assisted semen analysis, yet it remains challenging in microscopic images due to dense distribution

Stellar Colosseum: A Many-Agent Harness for Long-Horizon Research in Mathematics and Theoretical Computer Science

arXiv:2609.15983v1 Announce Type: new Abstract: Language models can produce plausible short proofs, but may still be unreliable on long-horizon research problems, where progress depends on a sequence

Structure-Token Evidence-Anchored Reasoning for Scientific Chart Understanding

arXiv:2609.13267v1 Announce Type: new Abstract: Scientific charts encode quantities in axes, legends, and geometric marks, yet large vision-language models still treat them as natural photographs. Vis

Sublinear Sketches for Approximate Nearest Neighbor and Kernel Density Estimation

arXiv:2510.23039v2 Announce Type: replace Abstract: Approximate Nearest Neighbor (ANN) search and Approximate Kernel Density Estimation (A-KDE) are fundamental problems at the core of modern machine l

Synthetic Leprosy Image Generation Using Mask-Conditioned Latent Diffusion and Transfer Learning from Large Chronic Wound Datasets

arXiv:2609.13226v1 Announce Type: new Abstract: Machine learning for neglected tropical diseases is limited by data, not algorithms: public annotated image sets for leprosy (Hansen's disease) number i

researcharxiv-cs-cv

Talking to Me or Someone Else? Rethinking Talk-to-Me Detection in Egocentric Videos

arXiv:2609.14118v1 Announce Type: cross Abstract: Online understanding of who is talking to the camera wearer is a key capability for egocentric social interaction. However, existing talk-to-me (TTM)

Safety

To do(x) or not to do(x): Medical Image Counterfactuals for Dataset Augmentation

arXiv:2609.14124v1 Announce Type: cross Abstract: Medical image analysis is often hindered by biased datasets, which can lead to biased models and limited clinical applicability. A promising strategy

safetyarxiv-cs-ai

v0.34.1

model-releasesollama-releases

What's Changed app: fix ChatGPT model selector spacing mlxrunner: Evict prefix cache snapshots from the active conversation mlxrunner: check system free memory and wait for evicted runners before load

When the Wrong Key Wins: Understanding and Detecting Hallucinations in LLMs

arXiv:2609.15106v1 Announce Type: new Abstract: Large language models can hallucinate even when the knowledge required for a correct answer is already available. We study this failure through a latent

researcharxiv-cs-cl

Local Ai

A Differentially Private Federated Proximal Optimization Framework for Customer Churn Prediction in Heterogeneous Federated Telecom Networks

arXiv:2609.12470v1 Announce Type: new Abstract: Customer churn is one of the major issues in the telecommunication industry. To predict customer churn, conventional centralized machine learning approa

local-aiarxiv-cs-lg

Adaptive Chemotherapy Control under Tumor Heterogeneity via Reinforcement Learning

arXiv:2609.12264v1 Announce Type: new Abstract: Designing effective chemotherapy regimens is hindered by tumor heterogeneity and drug resistance, which complicate the deployment of patient-specific mo

Announcing Pause/Resume and NVIDIA RTX PRO 6000 Blackwell GPU support in Dataflow

model-releasesgoogle-cloud-ai

OverviewAs enterprises scale their AI and agentic workflows, they require serverless platforms that make data preparation for model training, evaluation, and inference effortless and efficient. Datafl

AnyView: Synthesizing Any Novel View in Dynamic Scenes

arXiv:2601.16982v2 Announce Type: replace Abstract: Modern generative video models excel at producing convincing, high-quality outputs, but struggle to maintain multi-view and spatiotemporal consisten

BodhiPromptShield: Pre-Inference Prompt Mediation for Surface-Form Privacy Propagation in LLM Agent Pipelines

arXiv:2604.05793v2 Announce Type: replace-cross Abstract: In LLM agent pipelines, prompt privacy risk propagates beyond a single model call: raw user content enters retrieval queries, memory writes, t

Agents

Diverse Minds, Divided Networks? Personality Composition, Polarization, and Collective Intelligence in LLM-Based Social Simulations

arXiv:2609.12444v1 Announce Type: cross Abstract: Simulated societies of large language model agents are used to study online polarization, and separately to study collective intelligence, but the two

agentsarxiv-cs-cl

Do LLMs Trust the Accuser or the Accusation? Measuring Belief Shifts in Werewolf

arXiv:2609.12446v1 Announce Type: cross Abstract: Social-deduction games such as Werewolf are increasingly used to evaluate LLM agents, but existing evaluations often rely on final game outcomes. We p

EventMemAgent: Hierarchical Event-Centric Memory for Online Video Understanding with Adaptive Tool Use

arXiv:2602.15329v2 Announce Type: replace Abstract: Online video understanding requires models to perform continuous perception and long-range reasoning within potentially infinite visual streams. Its

ExpertHTR: Unified Handwritten Text Recognition with Multi-Task Learning and Sparse Mixture-of-Experts

arXiv:2609.12705v1 Announce Type: new Abstract: Handwritten text recognition resources are often small and distributed across collections that differ in language, script, document structure, and annot

Google is a leader in The Forrester Wave™: Public Cloud Platforms, Q3 2026

model-releasesgoogle-cloud-ai

We are excited to share that Google Cloud was named a Leader and received the highest score in the ‘current offering’ category in the Forrester Wave™: Public Cloud Platforms, Q3 2026 report, which exa

GSO-Net: Visual State Machines for Hazardous Freight Transfer Compliance at Petrochemical Logistics Nodes

arXiv:2609.12408v1 Announce Type: new Abstract: Hazardous-freight operations at petrochemical logistics nodes are safety-critical for intelligent transportation systems, yet existing vision benchmarks

KoSimpleQA: A Korean Factuality Benchmark with an Analysis of Reasoning LLMs

arXiv:2510.18368v2 Announce Type: replace Abstract: We present extbf{Korean SimpleQA (KoSimpleQA)}, a benchmark for evaluating factuality in large language models (LLMs) with a focus on Korean cultura

Local Edits, Global Ripples: Replay-Informed Policy Adaptation for Workflow Synthesis

arXiv:2609.12127v1 Announce Type: new Abstract: Prompt-policy editing offers a practical way to improve agents that synthesize executable workflows without updating the underlying model. However, pers

Membership Inference via Pairwise Likelihood Ratios

arXiv:2609.12367v1 Announce Type: cross Abstract: Membership inference attacks (MIAs) are the standard tool for auditing the privacy risks of machine learning models. Given a query point, an MIA aims

researcharxiv-cs-lg

MoPA: Coordinated Mobile Manipulation via Subsystem-Specific Perception Alignment

arXiv:2609.12081v1 Announce Type: cross Abstract: Mobile manipulation requires perceptual evidence at different spatial scales for base motion and arm control, while the two action modalities remain k

Residual Vector-based Reconstruction as Long-Context Recall Regardless of Context Window Size

arXiv:2609.12686v1 Announce Type: cross Abstract: Large language models (LLMs) process long contexts, including long documents and lengthy conversations, but face token-level memory usage that increas

RunningTensor: Generalizing Linear Attention to Higher-Order Recurrent States

arXiv:2609.12814v1 Announce Type: new Abstract: Linear attention and state-space models provide linear-time sequence modeling, but their recurrent memory remains a second-order tensor (a matrix), limi

researcharxiv-cs-lg

Tutorials

SAGE-Loop: Reliable Closed-Loop LLM-Driven AutoML with Trial-and-Correction and Adaptive Ensembling

arXiv:2609.12455v1 Announce Type: new Abstract: Automated machine learning (AutoML) is reshaping data-driven science and industrial practice, and as large language models are introduced into AutoML, p

tutorialsarxiv-cs-lg

Simulating Disengaged Students to Evaluate LLM-based Tutors

arXiv:2609.12331v1 Announce Type: new Abstract: Simulated students generated by computational models provide a practical way to evaluate tutoring strategies and pedagogical approaches used by human an

VS-Splat: Voxel-Selective feed-forward Gaussian Splatting for end-to-end 3D object reconstruction from sparse-views

arXiv:2609.12343v1 Announce Type: new Abstract: Feed-forward Gaussian splatting models have demonstrated remarkable effectiveness in reconstructing three-dimensional (3D) objects from a few two-dimens

Aurora1.0-150M Releases!