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SPAR-K: Scheduled Periodic Alternating Early Exit for Spoken Language Models

arXiv:2603.09215v2 Announce Type: replace Abstract: Interleaved spoken language models (SLMs) alternately generate text and speech tokens, but decoding at full transformer depth for every step becomes

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SpatialCrafter: Single Image World Modeling with Generative 3D Proxies

DGX agent

arXiv:2608.27073v1 Announce Type: new Abstract: Explorable image-to-scene generation is essential for applications in gaming, robotics, and virtual reality. Existing methods based on video diffusion m

model-releasesarxiv-cs-cv

28 Aug 2026

SPEAR: Distilling Domain-Adaptive Reasoning Skeletons via Sequential Symbolic Alignment in Reinforcement Learning

arXiv:2608.26550v1 Announce Type: new Abstract: Reinforcement learning-based knowledge distillation has the potential to transfer complex reasoning from teacher to student models, yet it currently fac

safetyarxiv-cs-cl

SpeechGym: An Audio-Native Gym for Training Voice Agents via Reinforcement Learning

arXiv:2608.26432v1 Announce Type: cross Abstract: Voice agents must call tools and hold multi-turn dialogue entirely through speech, yet the dominant paradigm trains them in text. Existing frameworks

Agents

SPT: Skills as Pre-Training Data for Agentic Language Models

arXiv:2608.26563v1 Announce Type: new Abstract: Agentic (tool-using) language models are mainly trained on tool-call traces and agent trajectories during post-training. These data provide direct behav

agentsarxiv-cs-cl

Squeezing More from Limited Data with Recursive Transformers

model-releasesarxiv-cs-cl

arXiv:2608.26973v1 Announce Type: new Abstract: Pre-training under limited data requires a different view of scaling than web-scale language modeling. With a fixed data budget but relatively abundant

SSMB: Self-Supervised Local Feature Detection under Motion Blur

arXiv:2608.27181v1 Announce Type: new Abstract: Keypoint detection under motion blur remains a significant challenge, as blur distorts local image structure and degrades the repeatability of feature l

safetyarxiv-cs-cv

Stable but Wrong: When Learning Stabilizes Away from the Truth

arXiv:2603.21491v2 Announce Type: replace Abstract: Stable training is often treated as evidence that learning is succeeding, but stability characterizes optimization behavior rather than correctness

safetyarxiv-cs-lg

Stack Trace-Based Crash Deduplication with Transformer Adaptation

arXiv:2508.19449v2 Announce Type: replace-cross Abstract: Automated crash reporting systems generate large volumes of duplicate reports, overwhelming issue-tracking systems and increasing developer wo

safetyarxiv-cs-lg

Stageboost: Recommending Signals Based on Counterfactual Estimation

arXiv:2608.27366v1 Announce Type: cross Abstract: Signals are short textual or visual snippets displayed on the eBay View-Item (VI) page, providing additional, contextual information for users about t

Local Ai

Standalone LLM and a Pre-specified Agentic Pipeline for Explaining ICU Mortality Predictions: a Feasibility Study on the eICU Demo Dataset

arXiv:2608.26109v1 Announce Type: new Abstract: Machine-learning models can predict ICU mortality accurately, but feature-attribution methods alone rarely provide the clinical narrative needed for bed

local-aiarxiv-cs-ai

STAR : Sentence Translation Alignment Rate for Document-to-Document Machine Translation

arXiv:2608.27161v1 Announce Type: new Abstract: Large Language Models (LLMs) have enabled a shift from sentence-level to document-to-document (Doc2Doc) machine translation, promising improved global c

safetyarxiv-cs-cl

STEP: State-Aware Task Estimation and Planning with Multi-Modal LLMs for Human-Robot Collaboration

arXiv:2608.27225v1 Announce Type: cross Abstract: Effective human-robot collaboration in industrial settings requires robots to understand human intentions and assist with task planning, reducing work

STITCH-OPE: Trajectory Stitching with Guided Diffusion for Off-Policy Evaluation

arXiv:2505.20781v2 Announce Type: replace-cross Abstract: Off-policy evaluation (OPE) estimates the performance of a target policy using offline data collected from a behavior policy, and is crucial i

safetyarxiv-cs-lg

StreamAV-Bench: A Comprehensive Benchmark for Streaming Audio-Video Generation

model-releasesarxiv-cs-cv

arXiv:2608.26336v1 Announce Type: cross Abstract: Recent advancements in generative models are pushing video generation toward unbounded streaming audio-video generation for real-time interactive worl

Structured Evidence Routing for Incident Risk Prediction from Multimodal Longitudinal EHRs

arXiv:2608.26191v1 Announce Type: new Abstract: Incident risk prediction from longitudinal electronic health records (EHRs) is challenging because relevant signals are multimodal, weak in isolation, a

Style as a Confound: False Positives in AI Detection of Non-Native Academic Writing

arXiv:2608.26710v1 Announce Type: new Abstract: AI text detectors are increasingly employed in academic settings, but it remains unclear whether their outputs reflect AI authorship itself or broader l

safetyarxiv-cs-ai

Subgraph Filtering for Fair Graph Neural Networks

model-releasesarxiv-cs-lg

arXiv:2608.26437v1 Announce Type: new Abstract: Graph neural networks (GNNs) can exhibit unfair behavior even when sensitive attributes are excluded from node features, because graph topology and mess

Subspace Alignment for Vision-Language Model Test-time Adaptation

arXiv:2601.08139v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs), despite their extraordinary zero-shot capabilities, are vulnerable to distribution shifts. Test-time adaptation

safetyarxiv-cs-ai

Successive Capacity Growth: Task-Complexity-Driven Width and Depth Expansion for Vision Transformer Encoders in JEPA World Models

arXiv:2608.27367v1 Announce Type: cross Abstract: Joint-Embedding Predictive Architectures (JEPAs) for world modeling typically employ fixed-size Vision Transformer encoders that are over-provisioned

Local Ai

Surgical Alignment in Knowledge Graph Training for Clinical Diagnosis with Large Language Models

arXiv:2608.26587v1 Announce Type: new Abstract: Biomedical knowledge graphs (KGs) offer structured medical knowledge that can ground large language model (LLM) reasoning in clinical diagnosis applicat

local-aiarxiv-cs-cl

Surgical Video Generation From Diffusion to World Models: A Survey

arXiv:2608.26214v1 Announce Type: new Abstract: Surgical video data provides the primary training resource for models of intraoperative perception, surgical workflow understanding, and robotic decisio

safetyarxiv-cs-cv

Survival-Guided Length Control for Efficient Diffusion Language Models

arXiv:2608.26374v1 Announce Type: new Abstract: Diffusion language models (DLMs) generate text by iteratively denoising masked sequences, but standard decoding either fixes the sequence length or reli

Agents

SWE-Prime: Fewer Trajectories, Better Performance

arXiv:2608.27449v1 Announce Type: cross Abstract: To improve large language models' ability to resolve real-world software issues, prior work has focused on constructing large-scale agent trajectory d

agentsarxiv-cs-ai

Sycophancy Suppression Can Impair Rational Updating: Anti-Sycophancy Should Preserve the Ability to Update

arXiv:2608.26511v1 Announce Type: new Abstract: Large language models often exhibit sycophancy, revising their answers to align with users when users push back. Such answer flips, however, can arise f

SymbolLKG: Towards Verifiable Logical Reasoning via Logical Knowledge Graph and Symbolic Solvers

arXiv:2608.26836v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable proficiency in natural language understanding, yet they struggle with strict multi-step reason

Syntax vs. Semantics: How Transformers Learn Deep Dependencies

arXiv:2608.26139v1 Announce Type: cross Abstract: Large Language Models demonstrate remarkable syntactic fluency, yet the optimization dynamics governing their acquisition of deep semantic dependencie

SynthCharge: An Electric Vehicle Routing Instance Generator with Feasibility Screening to Enable Learning-Based Optimization and Benchmarking

arXiv:2603.03230v2 Announce Type: replace-cross Abstract: The electric vehicle routing problem with time windows (EVRPTW) extends the classical VRPTW by introducing battery capacity constraints and ch

Tutorials

Systematic Literature Review of Machine Learning Models and Applications for Text Recognition

arXiv:2608.26500v1 Announce Type: new Abstract: Optical Character Recognition (OCR) for text recognition using machine vision has significantly improved, particularly when handling heterogeneous textu

tutorialsarxiv-cs-cv

Tabular Deep Learning for Algorithmic Trading: Cross-Regime Bayesian Optimisation for Equity Signal Generation

arXiv:2608.27076v1 Announce Type: new Abstract: Algorithmic trading now represents a market exceeding $20 billion, where even marginal gains in signal robustness can translate into economically signif

researcharxiv-cs-lg

TabuLM: Morphology-Aware Tabular Pre-training for Low-Resource Languages

model-releasesarxiv-cs-cl

arXiv:2608.26923v1 Announce Type: new Abstract: We present TabuLM, the first language model pre-trained on Kinyarwanda tabular data. Kinyarwanda is a morphologically rich Bantu language spoken by over

TADP: Task-Aware Deformable Prediction for Single-Stage 3D Object Detection

arXiv:2608.27282v1 Announce Type: cross Abstract: Most single-stage 3D object detectors complete different tasks with the same extracted features. Nevertheless, it is impossible to project features in

Task-space model-based control of pneumatic soft actuators

arXiv:2608.27186v1 Announce Type: new Abstract: Soft actuators enable dexterous and compliant interaction, but closed-loop task-space control remains challenging due to strong nonlinearities, distribu

researcharxiv-cs-ro

Technical Comparative Benchmarking Study: Advanced AI Hybrid Methods for Renewable Energy Farm Optimization and Forecasting

arXiv:2608.26613v1 Announce Type: new Abstract: This study provides a comprehensive benchmarking of conventional machine learning (ML), ensemble learning, deep neural networks, recurrent architectures

researcharxiv-cs-lg

TelecomGPT-R1: A Unified Open-Source Reasoner for the Telecom Stack

arXiv:2608.26126v1 Announce Type: new Abstract: Telecommunications is a high-leverage domain for large language model (LLM)-based reasoning because routine engineering workflows require joint groundin

safetyarxiv-cs-cl

TempJail: Temporal Jailbreak Attacks against Image-to-Video Generation Models

model-releasesarxiv-cs-cv

arXiv:2608.26971v1 Announce Type: new Abstract: In recent years, image-to-video (I2V) generation models have made remarkable progress in subject consistency and temporal coherence, enabling high quali

TEMPLAR Wales: A georeferenced environmental and toponymic dataset of Welsh settlements

arXiv:2608.26970v1 Announce Type: cross Abstract: Place names provide persistent records of how landscapes have been described and organised, but their quantitative reuse requires explicit separation

Temporal Sensitivity Analysis of Tessera Embeddings

arXiv:2608.27175v1 Announce Type: new Abstract: Many Earth Observation applications need land-use/land-cover maps that are both precise and frequently updated, yet the strongest Earth Observation foun

researcharxiv-cs-cv

TemporalFlow-VLA: Learning Physically Grounded Execution History for Long-Horizon Robot Manipulation

arXiv:2608.26821v1 Announce Type: new Abstract: Vision-language-action (VLA) models leverage pretrained vision-language representations for robot control, yet simply adding historical frames does not

researcharxiv-cs-ro

Temporally-Grounded Language Generation: Towards Real-Time Vision-Language Models

arXiv:2505.11326v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) have shown remarkable progress in offline tasks such as image captioning and video question answering. However,

Applications

Tensegrity Continuum Robots Enable Task-Adaptive Morphologies for Cooperative Behaviors

arXiv:2608.27221v1 Announce Type: new Abstract: Robots that can change their morphologies and behaviors for different tasks and environments hold great promise for adaptable, multifunctional systems.

applicationsarxiv-cs-ro

Terrain signatures in Welsh settlement names

arXiv:2608.26978v1 Announce Type: cross Abstract: Landscapes are named, but whether names retain measurable environmental information beyond broad geographic structure is rarely tested. We analysed 3,

Tether the Subject, Release the Scene: Query-Aware Memory Routing for Long-Horizon Autoregressive Video Generation

arXiv:2608.26902v1 Announce Type: new Abstract: Streaming autoregressive video models generate long videos chunk by chunk, using historical memory to maintain consistency. Existing methods typically e

researcharxiv-cs-cv

Text-to-seed generation: Training-free open-vocabulary seeded semantic segmentation via re-purposing diffusion as text-guided seed generator

arXiv:2608.26624v1 Announce Type: new Abstract: Open-vocabulary semantic segmentation (OVSS) aims to segment image regions corresponding to arbitrary text queries. Although the Segment Anything Model

researcharxiv-cs-cv

Local Ai

The Accuracy-Efficiency Paradox Quantifying Net Energy Loss in on-Device Energy Forecasting

arXiv:2608.26134v1 Announce Type: new Abstract: Energy forecasting aims to maximize accuracy to ensure energy efficiency by reducing energy waste, an objective that applies equally to on-device foreca

local-aiarxiv-cs-ai

The Artificial Experimentalist: Discovery and Control of Self-Organizing Phenomena with Autotelic Reinforcement Learning

arXiv:2608.26116v1 Announce Type: new Abstract: Existing methods for exploring cellular automata and other complex systems mostly operate in open loop: they set initial conditions, execute a full simu

safetyarxiv-cs-ai

Tutorials

The BS-meter: Detecting Politics and Labour through ChatGPT's Language

arXiv:2411.15129v3 Announce Type: replace-cross Abstract: What can we learn about language from studying how it is used by ChatGPT and other large language model (LLM)-based chatbots? In this paper, w

tutorialsarxiv-cs-ai

The Cold-Start Safety Gap in LLM Agents

model-releasesarxiv-cs-cl

arXiv:2606.07867v2 Announce Type: replace Abstract: Are tool-calling LLM agents equally safe throughout a conversation? We discover they are not: agents are most vulnerable at the very start of a sess