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S2MAM: Semi-supervised Meta Additive Model for Robust Estimation and Variable Selection

arXiv:2604.19072v1 Announce Type: cross Abstract: Semi-supervised learning with manifold regularization is a classical framework for jointly learning from both labeled and unlabeled data, where the ke

applicationsarxiv-cs-ai

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Safe Continual Reinforcement Learning in Non-stationary Environments

DGX agent

arXiv:2604.19737v1 Announce Type: new Abstract: Reinforcement learning (RL) offers a compelling data-driven paradigm for synthesizing controllers for complex systems when accurate physical models are

model-releasesarxiv-cs-lg

22 Apr 2026

Safety-Critical Contextual Control via Online Riemannian Optimization with World Models

arXiv:2604.19639v1 Announce Type: cross Abstract: Modern world models are becoming too complex to admit explicit dynamical descriptions. We study safety-critical contextual control, where a Planner mu

SafetyALFRED: Evaluating Safety-Conscious Planning of Multimodal Large Language Models

arXiv:2604.19638v1 Announce Type: new Abstract: Multimodal Large Language Models are increasingly adopted as autonomous agents in interactive environments, yet their ability to proactively address saf

SAGE-32B: Agentic Reasoning via Iterative Distillation

arXiv:2601.04237v2 Announce Type: replace Abstract: We demonstrate SAGE-32B, a 32 billion parameter language model that focuses on agentic reasoning and long range planning tasks. Unlike chat models t

SAGE: Training-Free Semantic Evidence Composition for Edge-Cloud Inference under Hard Uplink Budgets

arXiv:2604.19623v1 Announce Type: cross Abstract: Edge-cloud hybrid inference offloads difficult inputs to a powerful remote model, but the uplink channel imposes hard per-request constraints on the n

SAHM: A Benchmark for Arabic Financial and Shari'ah-Compliant Reasoning

arXiv:2604.19098v1 Announce Type: cross Abstract: English financial NLP has progressed rapidly through benchmarks for sentiment, document understanding, and financial question answering, while Arabic

SAMoRA: Semantic-Aware Mixture of LoRA Experts for Task-Adaptive Learning

arXiv:2604.19048v1 Announce Type: cross Abstract: The combination of Mixture-of-Experts (MoE) and Low-Rank Adaptation (LoRA) has shown significant potential for enhancing the multi-task learning capab

SAVOIR: Learning Social Savoir-Faire via Shapley-based Reward Attribution

arXiv:2604.18982v1 Announce Type: new Abstract: Social intelligence, the ability to navigate complex interpersonal interactions, presents a fundamental challenge for language agents. Training such age

SAW-INT4: System-Aware 4-Bit KV-Cache Quantization for Real-World LLM Serving

arXiv:2604.19157v1 Announce Type: new Abstract: KV-cache memory is a major bottleneck in real-world LLM serving, where systems must simultaneously support latency-sensitive small-batch requests and hi

applicationsarxiv-cs-lg

Scalable Memristive-Friendly Reservoir Computing for Time Series Classification

arXiv:2604.19343v1 Announce Type: cross Abstract: Memristive devices present a promising foundation for next-generation information processing by combining memory and computation within a single physi

Scheduling Analysis of UAV Flight Control Workloads using Raspberry Pi 5 Using PREEMPT_RT Linux

arXiv:2604.19275v1 Announce Type: cross Abstract: Modern UAV architectures increasingly aim to unify high-level autonomy and low-level flight control on a single General-Purpose Operating System (GPOS

researcharxiv-cs-ro

Scripts Through Time: A Survey of the Evolving Role of Transliteration in NLP

arXiv:2604.18722v1 Announce Type: new Abstract: Cross-lingual transfer in NLP is often hindered by the ``script barrier'' where differences in writing systems inhibit transfer learning between languag

researcharxiv-cs-cl

SCURank: Ranking Multiple Candidate Summaries with Summary Content Units for Enhanced Summarization

arXiv:2604.19185v1 Announce Type: cross Abstract: Small language models (SLMs), such as BART, can achieve summarization performance comparable to large language models (LLMs) via distillation. However

SEAT: Sparse Entity-Aware Tuning for Knowledge Adaptation while Preserving Epistemic Abstention

arXiv:2506.14387v3 Announce Type: replace Abstract: Adapting LLMs with new knowledge is increasingly important, but standard fine-tuning often erodes aligned epistemic abstention: the ability to ackno

See2Refine: Vision-Language Feedback Improves LLM-Based eHMI Action Designers

arXiv:2602.02063v2 Announce Type: replace-cross Abstract: Automated vehicles lack natural communication channels with other road users, making external Human-Machine Interfaces (eHMIs) essential for c

Seeing Candidates at Scale: Multimodal LLMs for Visual Political Communication on Instagram

arXiv:2604.19489v1 Announce Type: new Abstract: This paper presents a computational case study that evaluates the capabilities of specialized machine learning models and emerging multimodal large lang

applicationsarxiv-cs-cv

Local Ai

Self-Improving Tabular Language Models via Iterative Group Alignment

arXiv:2604.18966v1 Announce Type: cross Abstract: While language models have been adapted for tabular data generation, two fundamental limitations remain: (1) static fine-tuning produces models that c

local-aiarxiv-cs-ai

Semantic Interaction Information mediates compositional generalization in latent space

arXiv:2603.27134v3 Announce Type: replace Abstract: Are there still barriers to generalization once all relevant variables are known? We address this question via a framework that casts compositional

Semantic Needles in Document Haystacks: Sensitivity Testing of LLM-as-a-Judge Similarity Scoring

arXiv:2604.18835v1 Announce Type: cross Abstract: We propose a scalable, multifactorial experimental framework that systematically probes LLM sensitivity to subtle semantic changes in pairwise documen

Sentipolis: Emotion-Aware Agents for Social Simulations

arXiv:2601.18027v2 Announce Type: replace Abstract: LLM agents are increasingly used for social simulation, yet emotion is often treated as a transient cue, causing emotional amnesia and weak long-hor

Separating Geometry from Probability in the Analysis of Generalization

arXiv:2604.19560v1 Announce Type: new Abstract: The goal of machine learning is to find models that minimize prediction error on data that has not yet been seen. Its operational paradigm assumes acces

ShadowPEFT: Shadow Network for Parameter-Efficient Fine-Tuning

arXiv:2604.19254v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning (PEFT) reduces the training cost of full-parameter fine-tuning for large language models (LLMs) by training only a sma

Sherpa.ai Privacy-Preserving Multi-Party Entity Alignment without Intersection Disclosure for Noisy Identifiers

arXiv:2604.19219v1 Announce Type: cross Abstract: Federated Learning (FL) enables collaborative model training among multiple parties without centralizing raw data. There are two main paradigms in FL:

Hardware

Silicon Aware Neural Networks

arXiv:2604.19334v1 Announce Type: new Abstract: Recent work in the machine learning literature has demonstrated that deep learning can train neural networks made of discrete logic gate functions to pe

hardwarearxiv-cs-cv

SimDiff: Depth Pruning via Similarity and Difference

arXiv:2604.19520v1 Announce Type: new Abstract: Depth pruning improves the deployment efficiency of large language models (LLMs) by identifying and removing redundant layers. A widely accepted standar

SitEmb-v1.5: Improved Context-Aware Dense Retrieval for Semantic Association and Long Story Comprehension

model-releasesarxiv-cs-cl

arXiv:2508.01959v2 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) over long documents typically involves splitting the text into smaller chunks, which serve as the basic units f

SketchFaceGS: Real-Time Sketch-Driven Face Editing and Generation with Gaussian Splatting

arXiv:2604.19202v1 Announce Type: cross Abstract: 3D Gaussian representations have emerged as a powerful paradigm for digital head modeling, achieving photorealistic quality with real-time rendering.

Skillful Global Ocean Emulation and the Role of Correlation-Aware Loss

arXiv:2604.18727v1 Announce Type: cross Abstract: Machine learning emulators have shown extraordinary skill in forecasting atmospheric states, and their application to global ocean dynamics offers sim

SMART-Ship: A Comprehensive Synchronized Multi-modal Aligned Remote Sensing Targets Dataset and Benchmark for Berthed Ships Analysis

model-releasesarxiv-cs-cv

arXiv:2508.02384v2 Announce Type: replace Abstract: Given the limitations of satellite orbits and imaging conditions, multi-modal remote sensing (RS) data is crucial in enabling long-term earth observ

SmartPhotoCrafter: Unified Reasoning, Generation and Optimization for Automatic Photographic Image Editing

arXiv:2604.19587v1 Announce Type: new Abstract: Traditional photographic image editing typically requires users to possess sufficient aesthetic understanding to provide appropriate instructions for ad

SmokeGS-R: Physics-Guided Pseudo-Clean 3DGS for Real-World Multi-View Smoke Restoration

model-releasesarxiv-cs-cv

arXiv:2604.05301v2 Announce Type: replace Abstract: Real-world smoke simultaneously attenuates scene radiance, adds airlight, and destabilizes multi-view appearance consistency, making robust 3D recon

SpanVLA: Efficient Action Bridging and Learning from Negative-Recovery Samples for Vision-Language-Action Model

arXiv:2604.19710v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models offer a promising autonomous driving paradigm for leveraging world knowledge and reasoning capabilities, especially

safetyarxiv-cs-cv

Sparse Network Inference under Imperfect Detection and its Application to Ecological Networks

arXiv:2604.18820v1 Announce Type: cross Abstract: Recovering latent structure from count data has received considerable attention in network inference, particularly when one seeks both cross-group int

applicationsarxiv-cs-lg

SpecAgent: A Speculative Retrieval and Forecasting Agent for Code Completion

arXiv:2510.17925v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) excel at code-related tasks but often struggle in realistic software repositories, where project-specific APIs an

Local Ai

Speculative End-Turn Detector for Efficient Speech Chatbot Assistant

arXiv:2503.23439v2 Announce Type: replace-cross Abstract: Spoken dialogue systems powered by large language models have demonstrated remarkable abilities in understanding human speech and generating a

local-aiarxiv-cs-ai

Hardware

SpikeMLLM: Spike-based Multimodal Large Language Models via Modality-Specific Temporal Scales and Temporal Compression

arXiv:2604.18610v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress but incur substantial computational overhead and energy consumption during

hardwarearxiv-cs-ai

SPRITE: From Static Mockups to Engine-Ready Game UI

arXiv:2604.18591v1 Announce Type: cross Abstract: Game UI implementation requires translating stylized mockups into interactive engine entities. However, current 'Screenshot-to-Code' tools often strug

Agents

ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving

arXiv:2604.19145v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have become central to autonomous driving systems, yet their deployment is severely bottlenecked by the massive computat

agentsarxiv-cs-ai

Stable-RAG: Mitigating Retrieval-Permutation-Induced Hallucinations in Retrieval-Augmented Generation

arXiv:2601.02993v4 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) has become a key paradigm for reducing factual hallucinations in Large Language Models (LLMs), yet little is kn

safetyarxiv-cs-cl

STAR-Teaming: A Strategy-Response Multiplex Network Approach to Automated LLM Red Teaming

arXiv:2604.18976v1 Announce Type: new Abstract: While Large Language Models (LLMs) are widely used, they remain susceptible to jailbreak prompts that can elicit harmful or inappropriate responses. Thi

safetyarxiv-cs-cl

StepFly: Agentic Troubleshooting Guide Automation for Incident Diagnosis

arXiv:2510.10074v2 Announce Type: replace Abstract: Effective incident management in large-scale IT systems relies on troubleshooting guides (TSGs), but their manual execution is slow and error-prone.

StochasTok: Improving Fine-Grained Subword Understanding in LLMs

arXiv:2506.01687v3 Announce Type: replace Abstract: Subword-level understanding is integral to numerous tasks, including understanding multi-digit numbers, spelling mistakes, abbreviations, rhyming, a

researcharxiv-cs-cl

StomaD2: An All-in-One System for Intelligent Stomatal Phenotype Analysis via Diffusion-Based Restoration Detection Network

arXiv:2604.18632v1 Announce Type: new Abstract: Stomata play a crucial role in regulating plant physiological processes and reflecting environmental responses. However, accurate and high-throughput st

Streaming Structured Inference with Flash-SemiCRF

arXiv:2604.18780v1 Announce Type: new Abstract: Semi-Markov Conditional Random Fields (semi-CRFs) assign labels to segments of a sequence rather than to individual positions, enabling exact inference

Streamliners for Answer Set Programming

arXiv:2604.19251v1 Announce Type: cross Abstract: Streamliner constraints reduce the search space of combinatorial problems by ruling out portions of the solution space. We adapt the StreamLLM approac

STReasoner: Empowering LLMs for Spatio-Temporal Reasoning in Time Series via Spatial-Aware Reinforcement Learning

model-releasesarxiv-cs-cl

arXiv:2601.03248v2 Announce Type: replace Abstract: Spatio-temporal reasoning in time series involves the explicit synthesis of temporal dynamics, spatial dependencies, and textual context. This capab

Local Ai

StrikeWatch: Wrist-worn Gait Recognition with Compact Time-series Models on Low-power FPGAs

arXiv:2510.24738v2 Announce Type: replace-cross Abstract: Running offers substantial health benefits, but improper gait patterns can lead to injuries, particularly without expert feedback. While prior

local-aiarxiv-cs-lg