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SFAD: Speculative Factuality-Aware Decoding

arXiv:2609.00796v1 Announce Type: new Abstract: As one of the most critical challenges in large language models, contextual faithfulness directly determines their reliability in knowledge-intensive ap

SG-AMP: Scene-Graph-Guided Active Perception and Semantics-Aware Motion Planning for Pepper Plants

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DGX agent

arXiv:2609.01579v1 Announce Type: new Abstract: We present SG-AMP, integrating robust depth completion with input-conditioned uncertainty, persistent panoptic mapping, plant scene-graph reasoning, and

researcharxiv-cs-ro

2 Sept 2026

Sharp Mixed Spectral Barron Regularity of Coulombic Many-Electron Wave Functions

arXiv:2609.00872v1 Announce Type: cross Abstract: We establish sharp mixed spectral Barron regularity for eigenfunctions of molecular Coulomb Hamiltonians. The mixed norm is a Fourier L^1 norm with on

researcharxiv-cs-lg

Sierpinski--Knopp Wasserstein Distance for Persistence Diagrams and Applications to 2-Wasserstein Approximation

model-releasesarxiv-cs-lg

arXiv:2609.01528v1 Announce Type: cross Abstract: This paper introduces the Sierpinski-Knopp (SK) Wasserstein distance, a fast metric between persistence diagrams. The SK-Wasserstein distance, denoted

Silence is Golden: Mitigating Hallucinations in Large Audio-Language Models via Layer-Weighted Vector Steering

model-releasesarxiv-cs-lg

arXiv:2510.12851v2 Announce Type: replace-cross Abstract: Large Audio-Language Models (LALMs) excel in Audio QA but often suffer from hallucinations ungrounded in the audio. To our knowledge, we are t

Simple Additions, Substantial Gains: Expanding Scripts, Languages, and Lineage Coverage in URIEL+

arXiv:2510.27183v3 Announce Type: replace Abstract: The URIEL+ linguistic knowledge base supports multilingual research by encoding languages through geographic, genetic, and typological vectors. Howe

SinkPruner: Sink-Free Visual Token Pruning for Multimodal Large Language Models

arXiv:2609.01004v1 Announce Type: cross Abstract: Despite their strong multimodal understanding ability, multimodal large language models (MLLMs) incur substantial computational overhead when processi

Skill Following: Evaluating Actual Skill Use in Retrieval-Enabled LLM Agents

arXiv:2609.00549v1 Announce Type: new Abstract: Large Language Model (LLM) agents increasingly rely on external skills, yet standard evaluations obscure whether retrieving these skills actually helps.

SlideBank: A Persistent Hierarchical Evidence Bank for Consistent Whole-Slide Reasoning

arXiv:2609.00342v1 Announce Type: new Abstract: Whole-slide images (WSIs) are challenging for vision-language reasoning because diagnostically relevant morphology is sparse, heterogeneous, and distrib

SlideMix: Enhancing Whole Slide Image Analysis via Multimodal Shuffling

arXiv:2609.00396v1 Announce Type: new Abstract: Histopathological whole slide images (WSIs) are central to cancer diagnosis, but their gigapixel scale, tissue heterogeneity, weak slide-level supervisi

Slow to See, Slow to Suppress: Understanding the Effects of Modality in Context-Memory Conflicts

arXiv:2609.00293v1 Announce Type: new Abstract: We investigate how vision-language models (VLMs) handle context-memory conflicts; that is, situations in which the model is given information in context

SMELT: Scaling Laws for Compute-Matched MoE Looped Transformers

arXiv:2609.01343v1 Announce Type: new Abstract: Looped Transformers increase effective depth by iterating a shared block of layers, but most evaluations compare at fixed model size, conflating archite

safetyarxiv-cs-lg

Socrates went Nuclear: Comparing Interaction Strategies for AI systems in a Learning Context using Brain Sensing

arXiv:2609.00584v1 Announce Type: new Abstract: Does unrestricted AI access bypass the cognitive effort required for learning, or does it streamline knowledge acquisition? This paper reports on a stud

Soft-Argmax for the Projective Plane via the Veronese Embedding

arXiv:2609.00521v1 Announce Type: new Abstract: From horizon detection to fibre structures in X-ray imaging, many vision tasks recover lines via peak detection in Hough space H=S^1imesR, the domain of

SoK: When Safe Agents Fail Together: The Security of Multi Agent LLM Systems

arXiv:2609.00595v1 Announce Type: cross Abstract: Safe agents can fail together. Multi-agent LLM systems (MAS) move information, state, decisions, and authority across principal boundaries, creating f

Solaris: Towards Interfaces That Are Generated, Not Coded

arXiv:2609.00776v1 Announce Type: cross Abstract: Digital interfaces are traditionally implemented through intermediate representations such as code, requiring their appearance and behavior to be spec

Tutorials

Solving In-Table Prediction Problems by Deep Neural Networks with Performance Evaluation Using Synthetic Data

arXiv:2609.01262v1 Announce Type: new Abstract: Tabular deep learning (TDL) leverages neural networks (NN) to extract patterns from tabular data. Traditional TDL methods follow a supervised learning p

tutorialsarxiv-cs-lg

Some Emotions Run Deeper: Layer-wise Probing and Causal Intervention in Large Language Models

arXiv:2609.01279v1 Announce Type: cross Abstract: Emotion is expressed in text along a wide spectrum, from surface lexical cues to inferences entangled with content. Most layer-wise analyses of emotio

Sources of Truth: A Multi-Platform, Multilingual Audit of Citations in AI Mental Health Information Queries

arXiv:2609.00319v1 Announce Type: cross Abstract: Online health information seeking is shifting from keyword search, where users consider a ranked list of links, to conversational systems that compose

researcharxiv-cs-cl

SOVER: Formal Certification of Optimization Reformulations via LLM-Assisted SMT Verification

arXiv:2609.00728v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown remarkable promise in translating and reformulating complex mathematical optimization problems across modeling l

Space Generative AI with Solar Energy Harvesting

arXiv:2609.01062v1 Announce Type: new Abstract: Satellites are emerging as promising platforms to extend generative artificial intelligence (AI) services to remote areas lacking terrestrial infrastruc

Spatial Autoregressive Modeling of DINOv3 Embeddings for Unsupervised Anomaly Detection

model-releasesarxiv-cs-cv

arXiv:2603.02974v2 Announce Type: replace Abstract: DINO models provide rich patch-level representations that have recently enabled strong performance in unsupervised anomaly detection (UAD). Most exi

SpatialGuard: Harness-Guided Verifiable Spatial Reasoning for Text-to-Image Generation

arXiv:2609.01582v1 Announce Type: new Abstract: Complex 3D spatial text to image generation requires models to convert natural language into stable visual geometry, not merely semantic appearance. Exi

safetyarxiv-cs-cv

Local Ai

Spawn Freely, Act Sparingly: Progressive Risk Vesting for Recursive LLM-Agent Trees

arXiv:2609.01035v1 Announce Type: new Abstract: Recursive LLM agents can broaden their search by spawning specialists. Some branches later request tools that send data or deploy code. When should a br

local-aiarxiv-cs-ai

SpecMind: Enabling Spectrum Intelligence via Multi-Agent Hybrid Retrieval-Augmented Generation

arXiv:2609.00427v1 Announce Type: new Abstract: The exponential growth of wireless devices is driving unprecedented spectrum demand, pushing spectrum management toward more fine-grained decisions acro

Spiking Patches: Asynchronous, Sparse, and Efficient Tokens for Event Cameras

arXiv:2510.26614v2 Announce Type: replace Abstract: We propose tokenization of events and present a tokenizer, Spiking Patches, specifically designed for event cameras. Given a stream of asynchronous

SpokenUS: A Spoken User Simulator for Task-Oriented Dialogue

arXiv:2603.16783v2 Announce Type: replace Abstract: Robust voice agents require exposure to the full diversity of how people interact through speech. However, obtaining enough spoken interactions is p

researcharxiv-cs-cl

Staged Linguistic Seeding: Grounded Query Expansion for Verified-Unit QA in AI Contact Centers

arXiv:2609.00844v1 Announce Type: new Abstract: Customer-service QA in an AI contact center (AICC) runs under deployment constraints that benchmark QA misses: tight voice-hotline latency and a high co

StainPresetNet: Stain Preset Network for Fast Multi-to-Multi Stain Normalization

arXiv:2609.01146v1 Announce Type: cross Abstract: Stain normalization reduces color variations caused by variations in staining protocols and imaging conditions, thereby enhancing computer-aided diagn

StateSwap: Probing Support-Elimination Hidden States in Multiple-Choice Questions

arXiv:2609.01081v1 Announce Type: cross Abstract: Large language models often answer the same multiple-choice question inconsistently when it is posed under support-oriented and elimination-oriented f

Stochastic complexity of vectors containing cluster structure

arXiv:2609.00084v1 Announce Type: new Abstract: This paper studies the problem of computing the stochastic probability (shortest code length) of the encoded vectors containing cluster structure using

researcharxiv-cs-lg

Stochastic Optimization of Tree Tensor Networks

model-releasesarxiv-cs-cv

arXiv:2609.00870v1 Announce Type: cross Abstract: Tensor networks, originally developed for quantum many-body physics, are promising models for machine learning. We derive stochastic Riemannian optimi

Streaming4D: Accelerate 4D World Models via Block-wise Video Generation and Incremental Reconstruction

arXiv:2609.00610v1 Announce Type: new Abstract: Current 4D generation paradigms are often bottlenecked by a sequential decoupling design: video is generated first, followed by 3D reconstruction, leadi

StreamScout: Learning When to Look Deeper for Streaming Video Understanding

arXiv:2609.00291v1 Announce Type: new Abstract: Streaming video understanding requires answering questions that arrive at arbitrary moments over an unbounded video stream. Existing systems primarily f

safetyarxiv-cs-cv

StudentSim: Training LLM-based Student Simulators

arXiv:2609.01591v1 Announce Type: new Abstract: AI tutors are most useful when they adapt to each student's strengths, weaknesses, and preferred guidance, but evidence about which guidance works for w

StudyBench: Can Self-Evolution Squeeze Textbooks for Olympiad Capability?

arXiv:2609.00787v1 Announce Type: new Abstract: Humans need to study only a handful of well-written textbooks to master a discipline and attempt its hardest problems. We argue that an ideal self-evolu

Subliminal Learning as Trait-Direction Drift: A Mechanism and Targeted Control under SFT Distillation

model-releasesarxiv-cs-lg

arXiv:2609.01091v1 Announce Type: new Abstract: Beyond intended capabilities, model distillation can transfer hidden traits from a teacher. A teacher biased by a system prompt can generate semanticall

Subspace Levenberg Marquardt Algorithms in Training Neural Networks

arXiv:2609.00789v1 Announce Type: new Abstract: The Levenberg-Marquardt (LM) algorithm is a well-known second-order method for rapid convergence and strong robustness when training small- to medium-si

researcharxiv-cs-lg

Subword Segmental BabyLMs: Learning to Tokenise for Sample-Efficient Pretraining

arXiv:2609.01151v1 Announce Type: new Abstract: In the standard LM training pipeline, subword tokenisation is applied as a preprocessing step. Subword segmental language modelling is an alternative pa

Superposed Latent Autoencoder

arXiv:2609.01158v1 Announce Type: cross Abstract: Autoencoders typically meet tight latent-memory budgets by making each latent representation smaller, sacrificing representational capacity. We ask a

SupraTok: Cross-Boundary Tokenization for Enhanced Language Model Performance

arXiv:2508.11857v3 Announce Type: replace-cross Abstract: Tokenization remains a persistent bottleneck in language modeling, especially when vocabulary learning is limited by whitespace boundaries. We

SurgiATM: A Physics-Guided Plug-and-Play Model for Deep Learning-Based Smoke Removal in Laparoscopic Surgery

arXiv:2511.05059v3 Announce Type: replace Abstract: During laparoscopic surgery, smoke generated by tissue cauterization can significantly degrade the visual quality of endoscopic frames, increasing t

safetyarxiv-cs-cv

Tutorials

SymFold: Synergizing Evolutionary and Structural Priors for Accurate Protein Inverse Folding

arXiv:2609.01353v1 Announce Type: new Abstract: Protein inverse folding aims to recover amino acid sequences for a given 3D protein structure, underpinning broad applications such as enzyme engineerin

tutorialsarxiv-cs-ai

Synthetic Worlds for Temporal Evaluation and Knowledge Updating in LLMs

arXiv:2609.00184v1 Announce Type: new Abstract: Large language models (LLMs) rely on static pretraining corpora, causing their knowledge to become outdated over time. Existing approaches for evaluatin

TacVLA: Contact-Aware Tactile Fusion for Robust Vision-Language-Action Manipulation

arXiv:2603.12665v3 Announce Type: replace Abstract: Vision-Language-Action (VLA) models have demonstrated significant advantages in robotic manipulation. However, their reliance on vision and language

safetyarxiv-cs-ro

Tutorials

Taming Modality Entanglement in Continual Audio-Visual Segmentation

arXiv:2510.17234v3 Announce Type: replace-cross Abstract: Recently, significant progress has been made in multi-modal continual learning, aiming to learn new tasks sequentially in multi-modal settings

tutorialsarxiv-cs-ai

Task-Specific Prompt with Global Context for Multi-Task Graph Pre-Training

arXiv:2609.00047v1 Announce Type: cross Abstract: Graph prompt learning is an effective paradigm to adapt pre-trained graph models to downstream tasks in low-resource scenarios. However, existing mult

Applications

Teaching Vision-Language Models to Use the Scale They Are Given: Label-Free Equivariance Training for Metric Physical Reasoning

arXiv:2609.00658v1 Announce Type: new Abstract: Metric questions about video require vision-language models to use supplied real-world references to convert visual measurements into physical units. Ye

applicationsarxiv-cs-cv