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Self-correction Optimization for Interleaved Multimodal Generation

arXiv:2610.10400v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have made significant progress in visual understanding and generation. However, generating interleaved image--t

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Human DGX agent

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Semantic-Aware Predictive Mapping for Exploration and Navigation

DGX agent

arXiv:2610.10382v1 Announce Type: new Abstract: Predictive mapping can support robotic exploration and navigation by estimating unseen geometric layouts from partial occupancy observations. However, o

researcharxiv-cs-ro

8 Oct 2026

SemanticFold: Latent Sequence Compression SeparatesLanguage Modeling, Decodability, and Reasoning

model-releasesarxiv-cs-cl

arXiv:2610.10304v1 Announce Type: cross Abstract: We study whether latent sequence compression of prompt prefixes preserves the capabilities that large language models rely on during inference. We int

Sensitive-Topic Leakage Through LLM Routing Metadata: Measurement and Mitigation

arXiv:2610.09981v1 Announce Type: cross Abstract: LLM routers pick a cheap or expensive model per request by its content, and many gateways and some cloud platforms can log that choice with content lo

SeOPD: Self-Evolving LLMs via Online Policy Distillation from Self-Generated Chain-of-Thought

arXiv:2609.33181v2 Announce Type: replace-cross Abstract: Recent advances in online policy self-distillation (OPSD) have demonstrated that large language models (LLMs) can improve their capabilities b

safetyarxiv-cs-cl

Seq-Flow: Efficient Probabilistic Forecasting with Self-Rollout Error Control

arXiv:2610.10440v1 Announce Type: new Abstract: Many scientific forecasting tasks require updating a distribution over future trajectories as new observations arrive. Conventional diffusion and flow m

Sequential Pretraining Favors Large Models

model-releasesarxiv-cs-lg

arXiv:2610.09611v1 Announce Type: new Abstract: Large neural networks often acquire capabilities that small models fail to learn. Does this stem from large models learning more representative features

SGF+: Decoupling Gradient Flows for Autoregressive Video Generation

arXiv:2610.10429v1 Announce Type: new Abstract: Autoregressive video generation requires denoising the current frames while writing their key-value representations as context for future predictions. H

safetyarxiv-cs-cv

Shaer: Controlled Arabic Poetry Generation with Meter Subform and Semantic Conditioning

arXiv:2610.09756v1 Announce Type: new Abstract: Classical Arabic poetry generation requires simultaneously satisfying semantic, linguistic, and fine-grained prosodic constraints. Existing systems typi

Applications

Shape-Bayes: Bayesian Inference of Structured Shapes under Visual Ambiguity

arXiv:2610.09032v1 Announce Type: new Abstract: Perceiving structured shapes, such as human faces, from pixels is an inherently ambiguous task in real-world conditions. Yet, shape inference is largely

applicationsarxiv-cs-cv

Shared Gaussianization: What Gaussian Regularizers Certify About Contrastive Learning, and What They Miss

arXiv:2610.10299v1 Announce Type: new Abstract: What can a distribution-matching regularizer such as SIGReg in LeJEPA certify about contrastive learning? We study shared Gaussianization (SG), a charac

Shared Geometry As A Rosetta Stone: Cross-Modal Alignment Without Paired Data

arXiv:2610.09411v1 Announce Type: cross Abstract: Multimodal representations enable zero-shot classification and retrieval, but aligning independently trained models usually requires large amounts of

safetyarxiv-cs-cv

Shared Low-rank Basis Factorization for Data-free Mixture-of-Experts Compression

model-releasesarxiv-cs-lg

arXiv:2610.09342v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) large language models decouple capacity from compute through sparse routing, but their large parameter count creates storage an

Shared-Roadmap Generation and Evaluator for Multi-Agent Path Planning Using Heterogeneous Graph Neural Network

arXiv:2610.09034v1 Announce Type: cross Abstract: Multi-agent path planning (MAPP) in continuous environments often relies on roadmaps to balance safety and search efficiency. However, traditional roa

Sharp Asymptotic Theory of Maximum Likelihood Estimation for Gaussian Processes with an RBF Kernel

arXiv:2610.10080v1 Announce Type: cross Abstract: Gaussian processes (GPs) are widely used across machine learning, spatial statistics, time-series analysis, optimization, Bayesian statistics, and sci

SiGNgapore - An Interactive Dataset for Sign-based Visual Navigation

arXiv:2610.09488v1 Announce Type: new Abstract: The future of autonomous robots in human-oriented environments depends on their ability to navigate in the absence of prebuilt maps; exploiting navigati

agentsarxiv-cs-ro

sk-bench: A Native-First Benchmark for Evaluating Large Language Models in Slovak

model-releasesarxiv-cs-cl

arXiv:2610.09152v1 Announce Type: new Abstract: Multilingual LLM benchmarks omit Slovak, a morphologically rich West Slavic language of five million speakers, or cover it only by machine translation.

SkillCycle: Co-Evolving Agent Policies and Skill Banks

arXiv:2610.09430v1 Announce Type: new Abstract: Internalizing external skills changes a language agent's capabilities and, with them, the value of its remaining guidance: rules can become redundant, m

safetyarxiv-cs-cv

SkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement Learning

arXiv:2602.08234v2 Announce Type: replace Abstract: Large Language Model (LLM) agents have shown stunning results in complex tasks, yet they often operate in isolation, failing to learn from past expe

SkillSandbox: Skill Verification via Dynamic Scenario Synthesis

arXiv:2610.10088v1 Announce Type: cross Abstract: Self-evolving agents distill task-solving experience into skills for future reuse, but these skills can encode incorrect procedures or non-transferabl

Slow Beats Fast at the Kesten-Stigum Threshold: Minimax, Fisher-Information and Belief-Propagation Characterizations of the Information-Computation Gap in Sparse Stochastic Block Models

arXiv:2610.08872v1 Announce Type: cross Abstract: We study community recovery in the sparse symmetric stochastic block model with q communities, average degree d and signal strength lambda through sta

SNR-Gated LSTM-Conditioned Diffusion Model for MIMO Channel Estimation

arXiv:2610.08977v1 Announce Type: new Abstract: Accurate and low latency channel estimation is critical for modern MIMO systems, particularly under mobility, where channels exhibit structured sparsity

SoccerNet-FoulRet: Retrieving Semantically Similar Soccer Foul Videos

model-releasesarxiv-cs-cv

arXiv:2610.09742v1 Announce Type: new Abstract: Refereeing decisions in professional soccer remain inconsistent because referees cannot easily compare a contentious foul against similar past cases. We

SoftSEEPS improves ML-based precipitation forecasting

arXiv:2610.09752v1 Announce Type: new Abstract: In this paper we have developed a differentiable approximation of the well-known SEEPS score, which we name SoftSEEPS. This allows the training of a Mac

SOTA: Stock Options Trading Agents Guided by Option-Implied Return Distributions

arXiv:2610.10407v1 Announce Type: cross Abstract: As option markets grow and AI advances, agentic systems for option trading are gaining increasing attention. Language-model-based agents can reason ov

Sparse Feature Policy Unlearning Mitigates State Hallucination in Vision-Language-Action Models

arXiv:2610.09496v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have shown strong generalization in robotic manipulation by leveraging rich representations from pretrained vision

Sparse Planning in Visual World Models via Cost Gradients

arXiv:2610.10274v1 Announce Type: new Abstract: Token-based world models enable fine-grained latent planning, but repeatedly processing large spatial token grids makes action search expensive. We intr

Sparsifying Stochasticity, Not Capacity: Partial Stochasticity via Deep Weight Factorization of Prior Scales

model-releasesarxiv-cs-lg

arXiv:2610.09886v1 Announce Type: cross Abstract: Bayesian neural networks need not be fully stochastic to be universal conditional density approximators, but it remains open which parameters should b

Spatial Induction Heads: In-Context Learning of Multidimensional Cellular Automata

arXiv:2610.09124v1 Announce Type: new Abstract: Induction heads provide a mechanistic account of in-context learning in sequential data, but existing theory largely assumes that the context relevant t

Tutorials

Spatial Latent Reasoning for Embodied Reference Understanding

arXiv:2610.09418v1 Announce Type: new Abstract: Pointing-gesture visual grounding requires connecting hand geometry with the visual identity and extent of a referred object. A central challenge for co

tutorialsarxiv-cs-cv

SpatialUQ: Post-Hoc Uncertainty Quantification from Spatial Consistency in Black-Box Vision Models

arXiv:2610.09498v1 Announce Type: new Abstract: Clinical vision models are often deployed as frozen black boxes with no access to internals, retraining, or ground truth at inference time. We introduce

Applications

Speech Emotion Recognition Using CNN and Its Use Case in Digital Healthcare

arXiv:2406.10741v2 Announce Type: replace-cross Abstract: The process of identifying human emotion and affective states from speech is known as speech emotion recognition (SER). This is based on the o

applicationsarxiv-cs-lg

Spend Bytes on Breadth: Precision-Count Trade-offs for Decode-Time KV Compression in Long Chain-of-Thought Reasoning

arXiv:2610.05685v2 Announce Type: replace Abstract: Reasoning models write most of their KV cache while decoding long chains of thought (CoT), so the cache has to be compressed online under a fixed me

SpikingVLA: Asynchronous Spiking Vision-Language-Action Models

arXiv:2610.09710v1 Announce Type: new Abstract: ANN-to-SNN conversion offers a practical route toward energy-efficient spiking Vision-Language-Action (VLA) models by bypassing the substantial cost of

SPIN: Shadow Predictive Indexer for Sparse Attention

arXiv:2610.09025v1 Announce Type: new Abstract: Indexer-based sparse attention reduces the cost of core attention by passing only a fixed, small number of important tokens to it. However, the indexer

agentsarxiv-cs-lg

SPLATIFY: Reproduce, Discover, Innovate! From Papers and Ideas to Trainable 3DGS Code

arXiv:2610.09116v1 Announce Type: new Abstract: The rapid growth of 3D Gaussian Splatting (3DGS) research demands significant effort to reimplement papers before building on them. We introduce SPLATIF

agentsarxiv-cs-cv

SPW-Nav: A Streaming Panoramic World Model for Language-Guided Navigation

arXiv:2610.08941v1 Announce Type: new Abstract: Language-guided panoramic video generation benefits various downstream applications, such as interactive 3D scene exploration, virtual reality experienc

agentsarxiv-cs-cv

Stability and Diversity of Networked Self-Consuming Generative Ecosystems

arXiv:2610.09409v1 Announce Type: new Abstract: The widespread deployment of generative AI has made it increasingly difficult to distinguish synthetic content from real data. Consequently, synthetic d

StableGrasp: Reconstructing Physically Stable Human Hand Grasps from Single Images

arXiv:2610.09195v1 Announce Type: new Abstract: Reconstructing a physically stable human grasp from a single RGB image is challenging because physically modeling grasps is itself difficult, and the pr

Stationary Bias and Extrapolation in Nonlinear Two-Timescale Stochastic Approximation

arXiv:2610.10246v1 Announce Type: new Abstract: Constant-step stochastic approximation generally has a nonzero stationary mean error that persists under time averaging. This paper studies that error f

Steering Follows Geometry, Not Labels: Emotion Directions in a Full-Duplex Speech Model

arXiv:2610.08887v1 Announce Type: new Abstract: Full-duplex voice agents need to modulate emotion and delivery during real-time conversations, when de-escalating a complaint, carrying urgency in dispa

Steerspeech: Activation Steering For Emotion Control In Generated Speech

arXiv:2610.10415v1 Announce Type: cross Abstract: Pretrained text-to-speech (TTS) models can generate expressive speech, but reliable inference-time emotion control remains challenging: prompts and re

STORK: Spatio-Temporal Observation of uterine contRactions via neural networKs

arXiv:2610.09598v1 Announce Type: new Abstract: Uterine contractions in fetal MRI are typically identified manually and discarded, limiting insights into contraction dynamics. We formalize Uterine Con

StoryBlender: Inter-Shot Consistent and Editable 3D Storyboard with Spatial-temporal Dynamics

arXiv:2604.03315v2 Announce Type: replace Abstract: Storyboarding is a core skill in visual storytelling for film, animation, and games. However, automating this process requires a system to achieve t

Applications

Stream-Based Active Learning with Cooperative Neural Networks for Data-Efficient Partial Inverse Design: An Automotive Glass Run Channel Case Study

arXiv:2610.09848v1 Announce Type: new Abstract: Inverse design in engineering often runs into a simple problem. Each labeled training sample must be produced through expensive simulation, so building

applicationsarxiv-cs-lg

STRIDE: Spatial-Temporal Representation for Interval-conditioned Disease Evolution in Longitudinal Glioblastoma MRI

arXiv:2610.08848v1 Announce Type: cross Abstract: Glioblastoma (GBM), an aggressive primary brain tumor, is routinely monitored with longitudinal MRI after treatment. Distinguishing stable disease (SD

STRIKE: Learning Visual State Transitions for Physical World Modeling

model-releasesarxiv-cs-cv

arXiv:2610.09514v1 Announce Type: new Abstract: Physical world modeling requires predicting how interactions change a scene, not merely generating coherent motion. We propose STRIKE, a framework that

Structure alone supports efficient visual computation in the Drosophila visual system

arXiv:2610.10023v1 Announce Type: cross Abstract: Understanding the extent to which measured synaptic wiring determines computation remains a central challenge. Here, we couple the proofread adult Dro