All entries

Rubrics as an Attack Surface: Stealthy Preference Drift in LLM Judges

arXiv:2602.13576v2 Announce Type: replace-cross Abstract: Evaluation and alignment pipelines for large language models increasingly rely on LLM-based judges, whose behavior is guided by natural-langua

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Runtime-Incremental Transformer for Reinforcement-Learning-Based Adaptive Control

DGX agent

arXiv:2609.13545v1 Announce Type: cross Abstract: Learning-based adaptive control of robotic manipulators with non-observable friction memory has been addressed by attention- based meta-controllers wh

safetyarxiv-cs-lg

15 Sept 2026

RxScribe Bench: A Multi-Axis Benchmark for Evaluating Vision-Language Models on Indian Outpatient Prescriptions

model-releasesarxiv-cs-cv

arXiv:2609.13280v1 Announce Type: new Abstract: Prescription transcription errors are not interchangeable. A model that fabricates a drug and a model that misreads a legible dose pose very different c

S3-Tracker: Self-Supervised Surgical Tissue Tracking With Contrastive Random Walks

arXiv:2609.14313v1 Announce Type: new Abstract: Robust point tracking in endoscopic videos is essential for computer-assisted intervention and autonomous robotic surgery, enabling continuous registrat

agentsarxiv-cs-cv

Safe Meta-Reinforcement Learning via Information Space Reachability

arXiv:2609.15915v1 Announce Type: new Abstract: Meta-reinforcement learning (meta-RL) enables agents to adapt to unseen tasks with limited experience. Despite its promise, the application of meta-RL i

safetyarxiv-cs-lg

Safety as a Constraint: Fine-Tuning a LLM Recommender to Explain Itself

arXiv:2609.13657v1 Announce Type: new Abstract: Traditional recommender systems are typically trained to predict what item users will interact with next, but not why. However, offering personalized ev

Safety Signals to Verify NetOps Agents with Action-Level Granularity

arXiv:2609.14422v1 Announce Type: new Abstract: Agentic Network Operations (NetOps) are an emerging paradigm promising to enable workload-aware, self-adjustable, and reliable autonomous networks. Whil

SAILOR: Solver-Assisted Interactive LLM-based Optimization Recovery

arXiv:2609.13945v1 Announce Type: new Abstract: Natural-language descriptions of optimization problems may be incomplete or vague about numerical information that a solver requires, including costs, c

Industry

Salesforce announces AIforce, unlocking the power of its platform using composable agents

Salesforce Inc. unveiled AIforce today during its Dreamforce user conference, a new artificial intelligence interface layer that brings the power of the company’s platform to where people use AI agent

industrysiliconangle

Salesforce debuts Koa, a specialized model built to reason about CRM data

model-releasessiliconangle

Salesforce Inc. said today at its annual user conference Dreamforce that it has partnered with Nvidia Corp. to train and release Koa, a specialized artificial intelligence model that’s custom built fo

Salesforce deepens its integrations with AWS and Google Cloud to support AI agents

Salesforce Inc. is stretching its data and artificial intelligence tentacles further into the public cloud, announcing expanded strategic integrations with both Amazon Web Services Inc. and Google Clo

applicationssiliconangle

Salesforce Koa: An Enterprise Language Model for Agentic Tool Use

arXiv:2609.15066v1 Announce Type: cross Abstract: We present Salesforce Koa, an enterprise language model built by post-training the open-weight Nemotron-3-Super-120B foundation model with reinforceme

SALUTE: Benchmarking and Adapting LLMs for the Defense Domain

model-releasesarxiv-cs-cl

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

SAM3D-Part: Interactive Part Selection and Generation from 3D Objects

arXiv:2609.15639v1 Announce Type: new Abstract: Part-level control is essential for modern 3D asset creation, where objects are frequently edited, reused, animated, or fabricated through their individ

safetyarxiv-cs-cv

Same path, different: a mechanistic comparison of looped and stacked transformer encoders on 12-lead ECG

model-releasesarxiv-cs-lg

arXiv:2609.15498v1 Announce Type: new Abstract: Recurrent Transformers reusing their weights rather than stacking L distinct layers are becoming widely adopted due to their parameter efficiency [1,2,3

Same Patient, Different Order: Action-Level Reliability of Clinical LLM Agents Under Repeated Runs

arXiv:2609.13582v1 Announce Type: cross Abstract: A clinical agent benchmark can report the same verdict on identical inputs while the agent files a materially different order on each run. Such agents

Sampling headroom is not selection gain: a compute-value audit of test-time scaling for video world models

arXiv:2609.13257v1 Announce Type: cross Abstract: Test-time scaling (TTS) can improve generation only when additional compute produces better candidates and the system can reliably identify them. This

SAMReg: SAM-enabled Image Registration with ROI-based Correspondence

arXiv:2410.14083v2 Announce Type: replace Abstract: This paper describes a new spatial correspondence representation based on paired regions-of-interest (ROIs), for medical image registration. The dis

applicationsarxiv-cs-cv

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

SAR-FAH: A Frequency-Adaptive Hybrid Network based on Neural ODEs for Structural-Preserving SAR Despeckling

arXiv:2511.05890v2 Announce Type: replace Abstract: Synthetic Aperture Radar (SAR) images are inherently degraded by speckle noise that severely limits their reliability in high-precision applications

researcharxiv-cs-cv

Scalability and Performance Evaluation of Federated Learning Frameworks: A Comparative Analysis

arXiv:2609.15681v1 Announce Type: cross Abstract: This paper presents a systematic examination and experimental comparison of the prominent Federated Learning (FL) frameworks FedML, Flower, Substra, a

applicationsarxiv-cs-ai

Scalable partial information decomposition for symptom networks via supervised embeddings

model-releasesarxiv-cs-lg

arXiv:2609.13203v1 Announce Type: new Abstract: Pairwise relationships among mental-health symptoms are routinely summarised asscalar edge weights, which cannot express whether two symptoms carry over

Hardware

Scaling Federated Learning Across Docker, Kubernetes, and Slurm with NVIDIA FLARE

NVIDIA FLARE separates persistent federation services from dynamically launched job workers, allowing each participating site to deploy federated learning jobs on Docker, Kubernetes, or Slurm without

hardwarenvidia-developer

Scaling Hindi Quantum Natural Language Processing through Automatic Pregroup Supertagging

arXiv:2609.13721v1 Announce Type: new Abstract: Quantum Natural Language Processing (QNLP) uses pregroup grammars to translate grammatical structure into diagrammatic representations and quantum circu

researcharxiv-cs-cl

Scaling Telco Autonomy: Leveraging GNNs with Distributed GraphFlow

model-releasesgoogle-cloud-ai

The telecommunications industry is currently undergoing a paradigm shift, moving from traditional manual human-driven operations to fully Autonomous Network Operations. Modern networks have grown incr

Schizophrenia Detection from EEG Signals: A Transformer Framework with Spectrogram Representation

arXiv:2609.14015v1 Announce Type: new Abstract: Schizophrenia is a serious psychiatric disorder that affects millions of people worldwide, and its diagnosis remains primarily dependent on clinical ass

ScorePrompts: Natural-Language Exploration of Symbolic Music Scores through Analysis

arXiv:2609.13291v1 Announce Type: cross Abstract: We present ScorePrompts, an interactive system in which users upload a score, receive natural-language descriptions of its musical structure, ask ques

researcharxiv-cs-cl

Local Ai

SCOUT-SLAM: Structurally-Coupled Dual Uncertainty-Aware 3DGS SLAM in the Wild

arXiv:2609.14634v1 Announce Type: new Abstract: Recently, 3D Gaussian Splatting SLAM (3DGS-SLAM) has gained significant momentum in simultaneous localization and 3DGS scene reconstruction. In real-wor

local-aiarxiv-cs-cv

SDUs DAISY: A Benchmark for Danish Culture

arXiv:2601.19930v2 Announce Type: replace-cross Abstract: We introduce Daisy, a factual knowledge benchmark for Danish cultural heritage, based on curated topics from the Danish Culture Canon 2006. Fo

SEA-Nav: Efficient Policy Learning for Safe and Agile Quadruped Navigation in Cluttered Environments

arXiv:2603.09460v2 Announce Type: replace Abstract: Efficiently learning safe and agile quadruped navigation in densely cluttered environments remains difficult: existing methods often lack safety and

safetyarxiv-cs-ro

Seeing What the Vehicle Sees: Video-Augmented Virtual Reality for Physical Autonomous Vehicles

arXiv:2609.13224v1 Announce Type: new Abstract: Autonomous vehicles are expected to improve road safety and efficiency, but passengers often remain uncertain about what the vehicle perceives and why i

safetyarxiv-cs-ro

Selecting k Paths with the Minimum Longest Path Length in the Stochastic Semi-Bandit Setting

arXiv:2609.14557v1 Announce Type: new Abstract: When performing parallel data transmission through a network using multiple paths, it is practically important to minimize the maximum transmission time

researcharxiv-cs-lg

Selective Tool Use for Agentic Change Visual Question Answering in Remote Sensing

arXiv:2609.14523v1 Announce Type: new Abstract: Change visual question answering (Change VQA) requires understanding semantic changes across bi-temporal remote sensing images. Although vision language

agentsarxiv-cs-cv

Self-Evolving AI for Humanoids: Mechanisms, Safety, and Evaluation of Post-Deployment Self-Improvement

model-releasesarxiv-cs-ro

arXiv:2609.13236v1 Announce Type: new Abstract: Humanoid robots are becoming an important part of embodied artificial intelligence, driven by advances in reinforcement learning for locomotion, world m

Self-Evolving Memory for Generative Recommendation

arXiv:2609.15598v1 Announce Type: cross Abstract: Generative recommendation has emerged as a promising end-to-end paradigm for personalized recommendation. However, user preferences continuously evolv

Self-Indexing Attention for Compression-Compatible Sparse Long-Context LLM Inference

arXiv:2609.13205v1 Announce Type: cross Abstract: Sparse long-context inference requires efficient token retrieval in both prefill and decode. Existing methods often use different retrieval strategies

researcharxiv-cs-cl

Self-Orchestrating Language Models: Leveraging Semantic Dependence for Efficient Inference

arXiv:2609.14850v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate impressive capabilities, but their deployment presents significant efficiency challenges. Autoregressive decodi

Semantic Fibers and Cross-Gram Interference: A Calculus of Safety Drift in Overcomplete Representations

arXiv:2609.14861v1 Announce Type: cross Abstract: A deployed language model may refuse a harmful request in English yet comply with its faithful translation, revealing a cross-lingual safety failure t

Semantic Knowledge Technologies: what the Semantic Web lost sight of, and what it never had

arXiv:2609.14121v1 Announce Type: new Abstract: The Semantic Web set out to give information a machine-interpretable form so that software could integrate and reason over it. Its standards became scie

agentsarxiv-cs-ai

Semantic Privacy Protection with Utility Preservation for 3D Point Clouds

model-releasesarxiv-cs-cv

arXiv:2609.13823v1 Announce Type: new Abstract: Point cloud data face serious semantic privacy risks during acquisition, transmission, and cross-institutional sharing. Existing methods mostly rely on

Semantic-TVM: Structure-Preserving Trustworthy Virtual Memory for Memory-Augmented and Tool-Using Agents

arXiv:2609.15011v1 Announce Type: new Abstract: Memory-augmented and tool-using agents expose exact private values when remote LLMs process retrieved memory, tool actions, and intermediate observation

Semiotic Relations and Proof Methods: A Cross-Genre Study of Argument Structure with Large Language Models

arXiv:2609.15194v1 Announce Type: new Abstract: When a direct proof of a statement S seems hard or even impossible to obtain, there may exist another statement (or set of statements) S^{*}, somehow re

applicationsarxiv-cs-cl

Sensory Precision Inference for Multimodal Arbitration under Uncertainty

arXiv:2609.15065v1 Announce Type: new Abstract: Autonomous agents operating on multisensory data cannot assume that all sensory modalities remain consistently informative. In real environments, sensor

agentsarxiv-cs-lg

SENTINEL: A Multi-Pathway Architecture for Detecting Living-Off-the-Land APT Attacks on Windows Command Lines

arXiv:2609.14593v1 Announce Type: cross Abstract: Living-Off-the-Land (LOTL) is the dominant evasion technique of Advanced Persistent Threat (APT) actors, exploiting legitimate Windows utilities to co

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

Sequential Adapter Stacking for Cross-Lingual Low-Resource ASR

model-releasesarxiv-cs-cl

arXiv:2609.15758v1 Announce Type: new Abstract: Extending large-scale multilingual automatic speech recognition (ASR) models to low-resource languages remains challenging. Model performance is skewed

SGWIB:Sliced Gromov-Wasserstein Information Bottleneck for Video Highlight Detection

arXiv:2609.13966v1 Announce Type: cross Abstract: Video highlight detection aims to identify temporally important segments that capture the most informative or engaging events in a video. Reliable pre

Local Ai

SH-WRNN: Implicit Spherical Harmonics Weight Field Routing Neural Networks for Asymmetric Edge Intelligence

arXiv:2609.14614v1 Announce Type: new Abstract: Deep learning architectures remain rigidly built upon traditional fully connected layers. While networks scale up, few challenge this foundational root.

local-aiarxiv-cs-lg