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SemPOI-RL: Aligning LLM Semantic Reasoning for Interpretable Out-of-Town POI Sequential Generation

arXiv:2608.30399v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit strong semantic reasoning and open-ended generation abilities, but aligning these abilities with structured seque

safetyarxiv-cs-ai

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Research

SemTrace: Source-Grounded Semantic Signatures for Tracing LLM Exposure to Protected Documents

DGX agent

arXiv:2608.29575v1 Announce Type: new Abstract: Large language models are increasingly used to read documents and produce downstream text, creating a provenance problem when the document owner cannot

researcharxiv-cs-cl

1 Sept 2026

Sense Once, Serve Many: Common-Trace Factorized Constrained PPO for Online Sensing-Session Consolidation in Multi-Tenant ISAC Networks

arXiv:2608.29256v1 Announce Type: cross Abstract: Integrated sensing and communication (ISAC) networks can serve compatible requests through shared sensing sessions, but consolidation couples admissio

safetyarxiv-cs-lg

Sensitivity-Constrained Neural Operators for Data-Efficient Forward and Inverse Modeling of Partial Differential Equation Systems

arXiv:2608.29888v1 Announce Type: new Abstract: Neural operators provide fast surrogates for partial differential equation (PDE) solvers, but their reliability can degrade for high-dimensional spatial

researcharxiv-cs-lg

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

researcharxiv-cs-lg

SePArate: Segmenting Patterns from Defects in Wafer Manufacturing Using Weak Supervision

arXiv:2608.30410v1 Announce Type: cross Abstract: In semiconductor manufacturing, defect analysis is essential, but manual inspection cannot scale. However, existing automated inspection methods remai

tutorialsarxiv-cs-ai

SeqAlign3DVG: A Sequence-Aligned Benchmark and Voxel Reasoning Framework for 3D Visual Grounding

arXiv:2608.30451v1 Announce Type: new Abstract: Image-based 3D visual grounding is critical for embodied agents, yet existing benchmarks suffer from loose text-observation alignment and neglect tempor

Sequential Trajectories and Simultaneous Blending: Multi-Emotion Modeling for Instruction-Following TTS

arXiv:2608.30325v1 Announce Type: new Abstract: Natural-language instructions enable flexible control of synthesized speech, yet emotional TTS systems primarily model a single utterance-level affect,

safetyarxiv-cs-cl

SERA-H: Super-Resolution of Sentinel Time Series for Fine-Scale Canopy Height Mapping

arXiv:2512.18128v4 Announce Type: replace Abstract: High-resolution mapping of canopy height is essential for forest management and biodiversity monitoring. Although recent studies have led to the adv

Applications

SGE: Semantically-Guided Exploration for Unstructured Environments via Image-Space Waypoint Sampling

arXiv:2608.29315v1 Announce Type: cross Abstract: This work introduces Semantically-Guided Exploration (SGE), a modular exploration framework for ground vehicles that integrates pixel-level semantic s

applicationsarxiv-cs-ai

SGM: Safety Glasses for Multimodal Large Language Models via Neuron-Level Detoxification

arXiv:2512.15052v4 Announce Type: replace-cross Abstract: Disclaimer: Samples in this paper may be harmful and cause discomfort. Multimodal large language models (MLLMs) enable multimodal understandin

SGPDFuse: Semantically-Guided Physics-Disentanglement General Multi-Modal Image Fusion

arXiv:2608.29220v1 Announce Type: new Abstract: Multimodal image fusion (MMIF) aims to integrate complementary sensor data into a single representation that preserves intrinsic scene reality while eli

safetyarxiv-cs-cv

SGRNet: Spatially Guided Radiology Network for Structured Radiological Reporting of Head and Neck Cancer

arXiv:2608.29153v1 Announce Type: new Abstract: Automated radiological report generation can alleviate clinical workloads and eliminate observer variability. However, standard free-text generation mod

safetyarxiv-cs-cv

SHADOWBENCH: Toward Reliable Automatic Evaluation of Semantic Alignment in Autoformalization

arXiv:2608.29270v1 Announce Type: cross Abstract: Autoformalization translates informal mathematical theorems into code for proof assistants such as Lean. A central challenge is that current evaluatio

SHAKE-GNN: Scalable Hierarchical Kirchhoff-Forest Graph Neural Network

model-releasesarxiv-cs-lg

arXiv:2509.22100v2 Announce Type: replace Abstract: Graph Neural Networks (GNNs) have achieved remarkable success across a range of learning tasks. However, scaling GNNs to large graphs remains a sign

Applications

SHAPE of Chain-of-Thought in Math Reasoning

arXiv:2608.28600v1 Announce Type: new Abstract: Large language models (LLMs) achieve strong performance on mathematical reasoning benchmarks, yet the mathematically meaningful skills underlying their

applicationsarxiv-cs-ai

ShardMemo: Scope-Before-Routing for Agentic Memory Retrieval

arXiv:2601.21545v2 Announce Type: replace Abstract: Agentic systems accumulate persistent memory across sessions, tools, and tasks, and a later request must retrieve from it under two distinct constra

agentsarxiv-cs-ai

Sharp Approximation Rates for Neural Networks with Affine Latent Parameterizations

model-releasesarxiv-cs-lg

arXiv:2608.31157v1 Announce Type: new Abstract: Many parameter-efficient methods generate the parameters of a large neural network from a low-dimensional latent representation. Given an architecture P

Sharp Restricted Isometry Thresholds for Global Minima of Rank-Restricted Matrix LASSO

arXiv:2608.29018v1 Announce Type: cross Abstract: We determine the sharp restricted isometry threshold for recovery at global minima of the rank-restricted matrix LASSO. For target rank r_{star}, if t

researcharxiv-cs-lg

SIC-Agents: Benchmarking and Building an Adaptive Simulator for Pediatric Serious Illness Communication Training

arXiv:2608.29481v1 Announce Type: new Abstract: Pediatric serious illness communication (SIC) is critically important, yet scalable communication training for clinicians remains limited. Compared with

Signed random Fourier features for fast density estimation with indefinite kernels

arXiv:2608.29265v1 Announce Type: cross Abstract: Kernel density estimation (KDE) is one of the most fundamental statistical estimators of density functions. Its direct implementation on a dataset of

tutorialsarxiv-cs-lg

SimCRAFT: Distilling Remote Sensing Agents via Synthetic Trajectories and Contextual Retrieval-Augmented Fine-Tuning

arXiv:2608.30277v1 Announce Type: new Abstract: The unprecedented surge in Earth observation data volume and diversity has exposed a critical bottleneck for traditional manual workflows, catalyzing th

agentsarxiv-cs-ai

SimGuide: Typed Multi-Context User Representations for Preference-Conditioned Agent Planning

arXiv:2608.24888v2 Announce Type: replace Abstract: Agents that act on a user's behalf must plan differently for different users, and increasingly do so from some structured representation of user con

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

researcharxiv-cs-ai

SingProbe Technical Report

arXiv:2608.30703v1 Announce Type: cross Abstract: Runtime guardrails are essential for reliable large language model (LLM) deployment, yet existing approaches typically rely on independent, external m

Singular Curvature in ReLU Training:Differentiation and the Gradient-Flow Limit Need Not Commute

arXiv:2608.30960v1 Announce Type: new Abstract: Gradient descent (GD) is explicit Euler for gradient flow, but a state-accurate continuous-time surrogate need not remain accurate after differentiation

agentsarxiv-cs-lg

SinLlama -- A Large Language Model for Sinhala

arXiv:2508.09115v5 Announce Type: replace Abstract: Low-resource languages such as Sinhala are often overlooked by open-source Large Language Models (LLMs). In this research, we extend an existing mul

SIR: Self-improving Red-teaming for Compute Use Agents

arXiv:2608.30207v1 Announce Type: cross Abstract: Computer use agents (CUAs) are vision-language models that perceive a screen and act on a real operating system through mouse, keyboard, and terminal,

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

researcharxiv-cs-cv

SkillForge: Compositional Skill Synthesis with Verification-in-the-Loop for Generating Formally Verified Dafny Programs

arXiv:2608.29841v1 Announce Type: new Abstract: Generating formally verified programs from natural language remains challenging: existing approaches either produce code in a single pass without recour

SkillRet: A Large-Scale Benchmark for Skill Retrieval in LLM Agents

arXiv:2605.05726v2 Announce Type: replace Abstract: As LLM agents are increasingly deployed with large libraries of reusable skills, selecting the right skill for a user request has become a critical

SkillZip Pro: Execution-Aware Dynamic Compression of Progressively Loaded Skills for Self-Evolving Agents

arXiv:2608.30785v1 Announce Type: new Abstract: Production agent skills are directory bundles, not isolated prompts. The root is loaded at activation; references, schemas, scripts, assets, and nested

agentsarxiv-cs-ai

SleepWalking: Privileged Representation Shaping for End-to-End Blind Locomotion in Legged Robots

arXiv:2608.30883v1 Announce Type: new Abstract: Partially observable locomotion requires a policy to act when task-relevant properties of the robot--environment state are not fully specified by instan

safetyarxiv-cs-ro

Sleight of Word Benchmark: Can Language Models Notice If Their Own Output Was Tampered With?

arXiv:2608.29921v1 Announce Type: cross Abstract: The output of a Language Model can be tampered with while the model is writing it. A simple test can thus be constructed by evaluating the model's per

Local Ai

Small Language Models as Judges for Rubric-Based Reinforcement Learning

arXiv:2608.30005v1 Announce Type: new Abstract: Rubric-based reinforcement learning extends RL beyond tasks with exact answers or rule-based verifiers by scoring responses against instance-specific cr

local-aiarxiv-cs-cl

Small Reward Models via Backward Inference

arXiv:2602.13551v3 Announce Type: replace Abstract: Reward models (RMs) play a central role throughout the language model (LM) pipeline, particularly in non-verifiable domains. However, the dominant L

researcharxiv-cs-cl

Small Updates, Big Doubts: Does Parameter-Efficient Fine-tuning Enhance Hallucination Detection ?

arXiv:2602.11166v2 Announce Type: replace-cross Abstract: Parameter-efficient fine-tuning (PEFT) methods are widely used to adapt large language models (LLMs) to downstream tasks and are often assumed

SMG: Semantic Motion Graph for Monocular Dynamic Gaussian Splatting

arXiv:2608.31023v1 Announce Type: new Abstract: We study dynamic Gaussian Splatting from monocular videos. While recent advancements in dynamic Gaussian splatting offer a promising foundation for mode

tutorialsarxiv-cs-cv

Applications

SMILE: Smooth Motion for Improved Long-Horizon VLA Execution

arXiv:2608.29432v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models reduce inference cost by executing multiple actions per call, but longer horizons often degrade accuracy because raw

applicationsarxiv-cs-ro

SmoothRL: Online Reinforcement Learning During Asynchronous Execution

arXiv:2608.29768v1 Announce Type: new Abstract: Deploying robot policies in the physical world requires satisfying two fundamental desiderata: reliability and smooth real-time execution. However, depl

safetyarxiv-cs-ro

SMOTE-VAR: An Uncertainty-Aware Oversampling Method for Predicting Depression Remission in University Students

arXiv:2608.30102v1 Announce Type: new Abstract: University students experience disproportionately high rates of common mental health conditions, such as depression, which can impair learning, social f

safetyarxiv-cs-lg

SnapBench: Benchmarking Snap-and-Ask Multimodal Retrieval for Mobile Interactions

arXiv:2608.29607v1 Announce Type: new Abstract: Mobile AI acts as a visual oracle, empowering users to snap a picture of something and ask for information. Snap-and-ask retrieval is now one of the mos

SNF-Bench: Separating Static Drift from Natural Flow in Long-Horizon Fixed-Camera Video Generation

arXiv:2608.28694v1 Announce Type: new Abstract: Long-horizon video generation is evaluated with whole-frame metrics that reward motion and temporal consistency. For fixed-camera nature scenes this cre

SocialReasonBench: A Video-QA Benchmark for Social Reasoning with Counterfactual Narrative Videos

arXiv:2608.30716v1 Announce Type: new Abstract: Recent advances in Large Multimodal Models (LMMs) have greatly improved video understanding, yet their ability to reason about human-centered social sit

SonicMaster: Towards Controllable All-in-One Music Restoration and Mastering

arXiv:2508.03448v4 Announce Type: replace-cross Abstract: Music recordings often suffer from audio quality issues such as excessive reverberation, distortion, clipping, tonal imbalances, and a narrowe

tutorialsarxiv-cs-ai

Industry

Sonos opens its platform to third-party AI assistants, upgrades Sonos 27voice assistant with an in-house LLM, and plans to let users create their own AI agents (Chris Welch/Bloomberg)

Chris Welch / Bloomberg: Sonos opens its platform to third-party AI assistants, upgrades Sonos 27voice assistant with an in-house LLM, and plans to let users create their own AI agents — As the compan

industrytechmeme

Source-Dependent Deference in Medical Imaging Agents Under Falsified Findings: A Pilot Audit

arXiv:2608.29800v1 Announce Type: new Abstract: Tool-using agents are being proposed for medical imaging, and their behaviour when a tool returns a false finding is largely unmeasured. We audit whethe

agentsarxiv-cs-cv

Industry

Source: OpenAI's Astra model uses 'recurrent depth', a technique that improves cost and performance but obscures the AI's reasoning, making it harder to monitor (The Information)

The Information: Source: OpenAI's Astra model uses “recurrent depth”, a technique that improves cost and performance but obscures the AI's reasoning, making it harder to monitor — OpenAI says its fort

industrytechmeme