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Scalable Frequency- and Length-Aware Subdocument Deduplication for Large Language Model Pretraining

arXiv:2608.03089v1 Announce Type: new Abstract: Large-scale pretraining corpora contain substantial duplicate content. Although document-level deduplication is widely used, removing subdocument-level

safetyarxiv-cs-cl

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Research

Scaling an Autoregressive Transformer for Single-Cell Generation

DGX agent

arXiv:2608.02961v1 Announce Type: cross Abstract: We study a self-supervised generation task for single-cell gene expression vectors: given a set of vectors from a cell type, we aim to generate additi

researcharxiv-cs-ai

5 Aug 2026

Schedule-Informed Temporal Fusion Forecasting of Hourly Airport Security-Checkpoint Throughput

arXiv:2608.02950v1 Announce Type: new Abstract: Checkpoint staffing requires accurate forecasts of when screening demand will occur, yet flight schedules record departure times rather than passenger a

SciRet: A Compute-Aware Empirical Study of Retrieval and Reranking for Scientific RAG

arXiv:2608.03860v1 Announce Type: cross Abstract: We introduce SciRet, a compute-aware empirical study of retrieval-augmented generation for scientific question answering over CORD-19. Rather than pro

ScoreField: Neural Inverse Scattering with Score-Based Generative Priors

arXiv:2608.02937v1 Announce Type: cross Abstract: Designing an effective electromagnetic inverse-scattering solver requires faithful enforcement of nonlinear full-wave physics together with an express

Screenshots or Tools? Eliciting Tool Use and Managing Multimodal Context in Hybrid GUI-MCP Computer-Use Agents

arXiv:2608.03327v1 Announce Type: new Abstract: Hybrid computer-use agents can act through screenshots or call text tools. We find that having a tool available does not settle which way the effect goe

Agents

Search, Inspect, Fetch: Exploiting Boolean Retrieval for Deep-Research Agents

arXiv:2608.02751v1 Announce Type: cross Abstract: Existing deep-research agents use a search-visit workflow that retrieves and reads whole pages, without considering the addressable structure that web

agentsarxiv-cs-ai

SeaSlides: Semantic Abstraction Layer for Agentic Slide Generation

arXiv:2608.03298v1 Announce Type: new Abstract: Agentic presentation generation must preserve source content, maintain coherent visual design, render specialized objects, and produce usable artifacts.

SeCo-SBIR: Semantically Consistent Prompt Learning for Zero-Shot Sketch-Based Image Retrieval

arXiv:2608.03120v1 Announce Type: new Abstract: Adapting CLIP for zero-shot sketch-based image retrieval (ZS-SBIR) via prompt learning faces a fundamental tension: the model must bridge the sketch-pho

researcharxiv-cs-cv

Secure AI Watermarking Framework for IP Protection in Multi-Tenant Cloud Platforms

arXiv:2608.02656v1 Announce Type: cross Abstract: The Secured data safe guard transaction with multi-tenant environments run on private-protected authenticate platforms runs by secured handed environm

Security-First Evaluation of Text-to-Terraform: Benchmarking LLMs and SLMs for Secure IaC Generation

arXiv:2608.02672v1 Announce Type: cross Abstract: Cloud misconfiguration remains a leading cause of security incidents, yet whether LLMs and SLMs can generate security-compliant Infrastructure-as-Code

Sedentary Behavior Classification for Wearable Sensors with a CNN-BiLSTM Model

arXiv:2608.02946v1 Announce Type: new Abstract: Accurate detection of sedentary behavior is important for studying health risks related to prolonged sitting, but posture-based classification remains c

SEER: A Self-Grounded Evidence Interface for Controlled Spatial Relation Classification

arXiv:2608.03631v1 Announce Type: new Abstract: Spatial relation questions require a model to identify the queried subject and object before comparing their layout. Yet a VLM can recognize both entiti

local-aiarxiv-cs-cv

Self-Guided Adaptive Safety Alignment: Synthesizing and Internalizing Guidelines in Reasoning Models

arXiv:2511.21214v4 Announce Type: replace-cross Abstract: Explicit safety policies can improve reasoning-model safety, but their effective coverage may lag behind evolving jailbreak strategies. We stu

Self-Organising Digital Circuits

arXiv:2608.02606v1 Announce Type: new Abstract: Fault tolerance in classical computing has traditionally relied on static strategies like hardware redundancy and error-correcting codes. Biological sys

Self-Supervised Representation-Guided Generative Dataset Distillation

arXiv:2608.03218v1 Announce Type: cross Abstract: Dataset distillation compresses a large training set into a compact synthetic set while retaining its downstream utility. Most existing methods target

Self-Supervised Uncalibrated Multi-View Video Anonymization in the Operating Room

arXiv:2602.02850v3 Announce Type: replace Abstract: Privacy preservation is a prerequisite for using video data in Operating Room (OR) research. Effective anonymization relies on the exhaustive locali

local-aiarxiv-cs-cv

Applications

Semantic Haptic Feedback Enhances Dexterous Robotic Teleoperation

arXiv:2608.02780v1 Announce Type: new Abstract: In robot teleoperation, haptic feedback can be used to help human operators accomplish dexterous manipulation tasks. However, existing haptic feedback m

applicationsarxiv-cs-ro

Sensitivity, Causality, and Repair Dissociate: A Layer-Wise Analysis of Perturbation Robustness and Its Scaling

arXiv:2608.03842v1 Announce Type: new Abstract: When a language model fails on surface-perturbed input (typos, OCR noise, homophones), 'which layer is responsible' has three natural operationalization

Separating quantum circuits from classical LLMs

arXiv:2608.03962v1 Announce Type: cross Abstract: Modern large language models - transformers and diffusion language models - are built around two canonical algorithmic tasks: prediction and generatio

SeqLLM: Augmenting LLMs with Behavioral-Sequence Modeling for High-Stakes Decisions at WeChat Pay

arXiv:2608.03063v1 Announce Type: new Abstract: Merchant risk control at large payment platforms screens tens of millions of merchants daily, where false positives harm legitimate merchants and false

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs

arXiv:2608.03573v1 Announce Type: new Abstract: Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL) exhibit fundamentally different behaviors in enhancing multi-task reasoning for large langu

SGFormer: Structure-Guided Transformer for Robust Local Feature Matching

arXiv:2608.03423v1 Announce Type: new Abstract: Local feature matching is a fundamental component of photogrammetry, enabling accurate image correspondence critical for tasks such as 3D reconstruction

local-aiarxiv-cs-cv

Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning

arXiv:2608.03378v1 Announce Type: cross Abstract: The development and testing of advanced aerial robots require experiments in controlled environments with tailored airflow profiles. This paper presen

Shielding for Higher-Order Safety

arXiv:2608.03662v1 Announce Type: new Abstract: Safety shields are runtime enforcement mechanisms that restrict the actions of a controller to guarantee safety. Classical shields are usually synthesis

ShielDroid: A Hybrid Approach Integrating Machine and Deep Learning for Android Malware Detection

arXiv:2608.03250v1 Announce Type: cross Abstract: The rapid advancement of modern technology has led to a significant increase in the use of smart devices, such as smartphones and tablets, resulting i

Shooting for Contact: Contact-Implicit Multiple Shooting for Dynamic Motion Retargeting

arXiv:2608.03116v1 Announce Type: new Abstract: Motion retargeting approaches often prioritize kinematic similarity over whole-body dynamics, contact consistency, and actuation limits, yielding refere

researcharxiv-cs-ro

Shorter Reasoning, Earlier Answers? An Evaluation of Reasoning Interfaces

arXiv:2608.03401v1 Announce Type: cross Abstract: Large language models often reason at length before answering, increasing cost and latency. Prompts and trained settings can shorten this reasoning, b

Should the Boundary Term Be Learned in Reflected Diffusion? Conormal Trace and Reflection Masking

arXiv:2608.03469v1 Announce Type: cross Abstract: We study score learning for reflected diffusion on bounded domains. Reflection keeps trajectories feasible but does not ensure that the learned score

Should We Type or Talk to LLM Agents? A Comprehensive Study of Voice and Keyboard Input Perturbations

arXiv:2608.03970v1 Announce Type: new Abstract: Human input reaches language models by typing or speaking, and each channel leaves a distinct signature: orthographic noise for keyboards; for voice, di

Simulation-free and finite-time diffusion model

arXiv:2608.03117v1 Announce Type: new Abstract: The performance of generative diffusion models is determined by the choice of the reference diffusion process connecting the empirical and prior distrib

SimulRAG: Simulator-based RAG for Grounding LLMs in Long-form Scientific QA

arXiv:2509.25459v2 Announce Type: replace Abstract: Large Language Models (LLMs) show promise in generating long-form scientific explanations that synthesize evidence and connect multiple factors. How

Single Canonical Prompts Underestimate LLM Safety's Surface-Form Sensitivity

arXiv:2608.02665v1 Announce Type: cross Abstract: A benchmark score is a measurement instrument, yet most benchmarks read each item at a single canonical surface form. We ask whether that reading is f

SKILL-KD: Contrastive Skill Distillation for LLM Agents

arXiv:2607.28048v2 Announce Type: replace Abstract: Skill-based prompting has become a practical mechanism for improving large language model (LLM) agents, yet existing skill acquisition methods often

local-aiarxiv-cs-ai

SkillTrace: Traversing a Query-Skill Graph for Composable LLM Agents

arXiv:2608.02356v2 Announce Type: replace Abstract: Large language model agents increasingly solve complex tasks by composing reusable skills from a library. To address this, the key challenge is not

SLAMFormer-infty: Infinite SLAM Transformer for Unbounded Frontend and Backend Processing

arXiv:2608.03429v1 Announce Type: new Abstract: We introduce the Infinite SLAM Transformer (SLAMFormer-infty), the first geometric transformer capable of supporting both long-range frontend and backen

researcharxiv-cs-cv

SlimVLM: Sensitivity-aware Dynamic Structured Pruning with Adaptive Visual Token Selection for Efficient Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2608.03580v1 Announce Type: new Abstract: While Vision-Language Models (VLMs) have demonstrated remarkable performance in processing and understanding both text and images, their large parameter

SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation

arXiv:2608.03092v1 Announce Type: cross Abstract: We aim to improve model performance in multi-reward reinforcement learning training process. Existing Group reward-Decoupled Normalization Policy Opti

Socially Grounded Agentic AI: Coordinating Plural Perspectives through Social Theory

arXiv:2608.03910v1 Announce Type: new Abstract: As AI systems are deployed across increasingly diverse social contexts, alignment can no longer be framed as the optimization of a single, unified set o

SocietyBench: Forecasting Counterfactual Social-World Evolution

arXiv:2608.04009v1 Announce Type: new Abstract: Large language models (LLMs), and the agents built on top of them, are now benchmarked heavily on whether they can finish a task -- fix a bug, drive a b

Tutorials

Soft Guidance Starts to Outperform CoT Prompting as LLMs Improve

arXiv:2608.03550v1 Announce Type: new Abstract: Chain-of-Thought (CoT) prompting remains the standard baseline for evaluating models' reasoning abilities. Originally, this technique was introduced to

tutorialsarxiv-cs-ai

Solver-Aware Decompositions for Programming-by-Example: When Dividing Requires Knowing how to Conquer

arXiv:2608.03461v1 Announce Type: new Abstract: Decomposition-based Programming-by-example (PBE) scales performance by splitting tasks into subtasks that a learned synthesizer solves: a decomposer pre

SP3O: Reinforcement Learning from Segment Preferences without Reward Modeling

arXiv:2608.02951v1 Announce Type: cross Abstract: Preference-based reinforcement learning (PbRL) for general stochastic MDPs often requires training a reward model. Existing reward-model-free methods

SPADE: An Input-Adaptive Sparse Attention Engine for Fast Video Diffusion Models Inference

arXiv:2608.03335v1 Announce Type: new Abstract: Video diffusion transformers (vDiTs) generate high quality but pay quadratic self-attention cost, making inference prohibitive at video-token scales. Th

safetyarxiv-cs-cv

Tutorials

Sparse Weight Decomposition for Efficient Circuit Extraction

arXiv:2608.03913v1 Announce Type: cross Abstract: Dense pretrained transformers do not naturally expose interpretable units for circuit extraction. Existing approaches obtain such units by learning au

tutorialsarxiv-cs-cl

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels

arXiv:2608.02995v1 Announce Type: cross Abstract: Modern large language models (LLMs) exhibit activation sparsity, wherein only a subset of their neurons is activated for given input tokens. Researche

Spatial proteomics guided by H&E-based AI reveals recurrence-risk niches in triple-negative breast cancer

arXiv:2608.03145v1 Announce Type: new Abstract: Deep learning models can predict cancer recurrence from H&E stained slides, but the localized molecular states underlying these predictions remain large

local-aiarxiv-cs-ai

SpatialCLI: Learning to Reason With Spatial Tools, Then Without Them

arXiv:2607.27703v2 Announce Type: replace Abstract: Vision-language models (VLMs) are increasingly used in embodied agents to interpret visual inputs, reason about spatial relationships, and make task