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River-LLM: Large Language Model Seamless Exit Based on KV Share

arXiv:2604.18396v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated exceptional performance across diverse domains but are increasingly constrained by high inference latency

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Robust Bias Evaluation with FilBBQ: A Filipino Bias Benchmark for Question-Answering Language Models

DGX agent

arXiv:2602.14466v2 Announce Type: replace Abstract: With natural language generation becoming a popular use case for language models, the Bias Benchmark for Question-Answering (BBQ) has grown to be an

model-releasesarxiv-cs-cl

21 Apr 2026

Robust Diabetic Retinopathy Grading Using Dual-Resolution Attention-Based Deep Learning with Ordinal Regression

arXiv:2604.17341v1 Announce Type: new Abstract: Diabetic retinopathy (DR) is a leading cause of vision impairment worldwide, and automated grading systems play a crucial role in large-scale screening

researcharxiv-cs-cv

Robust Tool Use via Fission-GRPO: Learning to Recover from Execution Errors

arXiv:2601.15625v2 Announce Type: replace Abstract: Large language models (LLMs) can call tools effectively, yet they remain brittle in multi-turn execution: after a tool-call error, smaller models of

RoIt-XMASA: Multi-Domain Multilingual Sentiment Analysis Dataset for Romanian and Italian

arXiv:2604.17134v1 Announce Type: new Abstract: We present RoIt-XMASA, a multilingual dataset that extends the Cross-lingual Multi-domain Amazon Sentiment Analysis to Italian and Romanian, comprising

RoMathExam: A Longitudinal Dataset of Romanian Math Exams (1895-2025) with a Seven-Decade Core (1957-2025)

arXiv:2604.16392v1 Announce Type: cross Abstract: AI in Education research increasingly relies on authentic, curriculum-grounded assessment data, yet large, well-structured exam corpora remain scarce

RosettaSearch: Multi-Objective Inference-Time Search for Protein Sequence Design

arXiv:2604.17175v1 Announce Type: new Abstract: We introduce RosettaSearch, an inference-time multi-objective optimization approach for protein sequence optimization. We use large language models (LLM

RoTRAG: Rule of Thumb Reasoning for Conversation Harm Detection with Retrieval-Augmented Generation

arXiv:2604.17301v1 Announce Type: new Abstract: Detecting harmful content in multi turn dialogue requires reasoning over the full conversational context rather than isolated utterances. However, most

Roundtables: Unveiling The 10 Things That Matter in AI Right Now

Listen to the session or watch below Watch a special edition of Roundtables simulcast live from EmTech AI, MIT Technology Review’s signature conference for AI leadership. Subscribers got an exclusive

researchmit-tech-review

Local Ai

RS-HyRe-R1: A Hybrid Reward Mechanism to Overcome Perceptual Inertia for Remote Sensing Images Understanding

arXiv:2604.17504v1 Announce Type: new Abstract: Reinforcement learning (RL) post-training substantially improves remote sensing vision-language models (RS-VLMs). However, when handling complex remote

local-aiarxiv-cs-cv

Rule-VLN: Bridging Perception and Compliance via Semantic Reasoning and Geometric Rectification

model-releasesarxiv-cs-cv

arXiv:2604.16993v1 Announce Type: cross Abstract: As embodied AI transitions to real-world deployment, the success of the Vision-and-Language Navigation (VLN) task tends to evolve from mere reachabili

Running AI from Cloud to Edge with Kubernetes: A Joint Approach from Vultr, Supermicro, and SUSE

This article discusses a collaborative approach from Vultr, Supermicro, and SUSE for deploying and managing AI workloads across cloud and edge computing environments using Kubernetes orchestration. Th

tutorialsvultr

Russia eased vaccination standards when diphtheria seemed beaten. 157,000 infections. 5,000 dead. Japan dropped mandates after a trust colla…

Russia eased vaccination standards when diphtheria seemed beaten. 157,000 infections. 5,000 dead. Japan dropped mandates after a trust collapse. Rubella came back. Babies born blind and deaf. Nigeria

researchyann-lecun--x

S-GRPO: Unified Post-Training for Large Vision-Language Models

arXiv:2604.16557v1 Announce Type: cross Abstract: Current post-training methodologies for adapting Large Vision-Language Models (LVLMs) generally fall into two paradigms: Supervised Fine-Tuning (SFT)

safetyarxiv-cs-cl

S2H-DPO: Hardness-Aware Preference Optimization for Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2604.18512v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have demonstrated remarkable progress in single-image understanding, yet effective reasoning across multiple images remain

Saccade Attention Networks: Using Transfer Learning of Attention to Reduce Network Sizes

arXiv:2604.16485v1 Announce Type: new Abstract: One of the limitations of transformer networks is the sequence length due to the quadratic nature of the attention matrix. Classical self attention uses

tutorialsarxiv-cs-cv

Saddle-To-Saddle Dynamics in Deep ReLU Networks: Low-Rank Bias in the First Saddle Escape

arXiv:2505.21722v2 Announce Type: replace Abstract: When a deep ReLU network is initialized with small weights, gradient descent (GD) is at first dominated by the saddle at the origin in parameter spa

Safe Control using Learned Safety Filters and Adaptive Conformal Inference

arXiv:2604.18482v1 Announce Type: cross Abstract: Safety filters have been shown to be effective tools to ensure the safety of control systems with unsafe nominal policies. To address scalability chal

SafeAnchor: Preventing Cumulative Safety Erosion in Continual Domain Adaptation of Large Language Models

arXiv:2604.17691v1 Announce Type: new Abstract: Safety alignment in large language models is remarkably shallow: it is concentrated in the first few output tokens and reversible by fine-tuning on as f

SafeLM: Unified Privacy-Aware Optimization for Trustworthy Federated Large Language Models

arXiv:2604.16606v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in high-stakes domains, yet a unified treatment of their overlapping safety challenges remains

SaFeR-Steer: Evolving Multi-Turn MLLMs via Synthetic Bootstrapping and Feedback Dynamics

arXiv:2604.16358v1 Announce Type: cross Abstract: MLLMs are increasingly deployed in multi-turn settings, where attackers can escalate unsafe intent through the evolving visual-text history and exploi

safetyarxiv-cs-cl

Safer Trajectory Planning with CBF-guided Diffusion Model for Unmanned Aerial Vehicles

arXiv:2604.17527v1 Announce Type: new Abstract: Safe and agile trajectory planning is essential for autonomous systems, especially during complex aerobatic maneuvers. Motivated by the recent success o

safetyarxiv-cs-ro

Safety, Security, and Cognitive Risks in State-Space Models: A Systematic Threat Analysis with Spectral, Stateful, and Capacity Attacks

arXiv:2604.16424v1 Announce Type: cross Abstract: State-Space Models (SSMs) -- structured SSMs (S4, S4D, DSS, S5), selective SSMs (Mamba, Mamba-2), and hybrid architectures (Jamba) -- are deployed in

safetyarxiv-cs-cl

SafeVLA: Towards Safety Alignment of Vision-Language-Action Model via Constrained Learning

model-releasesarxiv-cs-ro

arXiv:2503.03480v4 Announce Type: replace Abstract: Vision-language-action models (VLAs) show potential as generalist robot policies. However, these models pose extreme safety challenges during real-w

Same Claim, Different Judgment: Benchmarking Scenario-Induced Bias in Multilingual Financial Misinformation Detection

arXiv:2601.05403v2 Announce Type: replace Abstract: Large language models (LLMs) have been widely applied across various domains of finance. Since their training data are largely derived from human-au

Same prompts as before, but now in GPT image-generator 2, page excerpts from: 'Eldritch Horrors as Pets: A Guide' 'How Womblenauts Work' 'Ph…

tutorialsethan-mollick--x

Same prompts as before, but now in GPT image-generator 2, page excerpts from: 'Eldritch Horrors as Pets: A Guide' 'How Womblenauts Work' 'Photographs of the People of New York Who Look Like Birds' 'Ca

Sampling for Quality: Training-Free Reward-Guided LLM Decoding via Sequential Monte Carlo

arXiv:2604.16453v1 Announce Type: new Abstract: We introduce a principled probabilistic framework for reward-guided decoding in large language models, addressing the limitations of standard decoding m

researcharxiv-cs-lg

Sampling Matters: The Effect of ECG Frequency on Deep Learning-Based Atrial Fibrillation Detection

arXiv:2604.16437v1 Announce Type: cross Abstract: Deep learning models for atrial fibrillation (AF) detection are increasingly trained on heterogeneous electrocardiogram (ECG) datasets with varying sa

SAND: The Challenge on Speech Analysis for Neurodegenerative Disease Assessment

arXiv:2604.16445v1 Announce Type: cross Abstract: Recent advances in Artificial Intelligence (AI) and the exploration of noninvasive, objective biomarkers, such as speech signals, have encouraged the

researcharxiv-cs-cv

Agents

Satellite Chasers: Divergent Adversarial Reinforcement Learning to Engage Intelligent Adversaries on Orbit

arXiv:2409.17443v2 Announce Type: replace Abstract: As space becomes increasingly crowded and contested, robust autonomous capabilities for multi-agent environments are gaining critical importance. Cu

agentsarxiv-cs-ro

SAUVER LA FRANCE ET L'EUROPE EN FAISANT LE SEUL PARI QUI VAILLE (série banane rouge) I. COMME BONAPARTE : CONCENTRER LES FORCES, PAS LES DIL…

model-releasesyann-lecun--x

SAUVER LA FRANCE ET L'EUROPE EN FAISANT LE SEUL PARI QUI VAILLE (série banane rouge) I. COMME BONAPARTE : CONCENTRER LES FORCES, PAS LES DILUER Dans le discours politico-industriel d'aujourd'hui, on e

Hardware

Scalable and Adaptive Parallel Training of Graph Transformer on Large Graphs

arXiv:2604.16715v1 Announce Type: cross Abstract: Graph foundation models have demonstrated remarkable adaptability across diverse downstream tasks through large-scale pretraining on graphs. However,

hardwarearxiv-cs-lg

Scalable Neighborhood-Based Multi-Agent Actor-Critic

arXiv:2604.18190v1 Announce Type: new Abstract: We propose MADDPG-K, a scalable extension to Multi-Agent Deep Deterministic Policy Gradient (MADDPG) that addresses the computational limitations of cen

Scalable Physics-Informed Neural Differential Equations and Data-Driven Algorithms for HVAC Systems

arXiv:2604.18438v1 Announce Type: new Abstract: We present a scalable, data-driven simulation framework for large-scale heating, ventilation, and air conditioning (HVAC) systems that couples physics-i

Local Ai

Scalable Quantum Error Mitigation with Physically Informed Graph Neural Networks

arXiv:2604.16815v1 Announce Type: cross Abstract: Quantum error mitigation (QEM) provides a practical route for estimating reliable observables on noisy intermediate-scale quantum (NISQ) devices. Trad

local-aiarxiv-cs-lg

Scale-free adaptive planning for deterministic dynamics & discounted rewards

arXiv:2604.18312v1 Announce Type: new Abstract: We address the problem of planning in an environment with deterministic dynamics and stochastic rewards with discounted returns. The optimal value funct

researcharxiv-cs-lg

Agents

Scaling Beyond Context: A Survey of Multimodal Retrieval-Augmented Generation for Document Understanding

arXiv:2510.15253v3 Announce Type: replace Abstract: Document understanding is critical for applications from financial analysis to scientific discovery. Current approaches, whether OCR-based pipelines

agentsarxiv-cs-cl

Scaling Codex to enterprises worldwide

OpenAI's Codex, a code generation model trained on publicly available code, was scaled for enterprise deployment to provide developers with AI-assisted coding capabilities across organizations worldwi

model-releasesopenai

Scaling External Knowledge Input Beyond Context Windows of LLMs via Multi-Agent Collaboration

arXiv:2505.21471v2 Announce Type: replace Abstract: With the rapid advancement of post-training techniques for reasoning and information seeking, large language models (LLMs) can incorporate a large q

Scaling Human-AI Coding Collaboration Requires a Governable Consensus Layer

arXiv:2604.17883v1 Announce Type: cross Abstract: Vibe coding produces correct, executable code at speed, but leaves no record of the structural commitments, dependencies, or evidence behind it. Revie

Scaling Recurrence-aware Foundation Models for Clinical Records via Next-Visit Prediction

arXiv:2603.24562v2 Announce Type: replace Abstract: While large-scale pretraining has revolutionized language modeling, its potential remains underexplored in healthcare with structured electronic hea

Scaling Test-Time Compute for Agentic Coding

arXiv:2604.16529v1 Announce Type: cross Abstract: Test-time scaling has become a powerful way to improve large language models. However, existing methods are best suited to short, bounded outputs that

Scaling up Kimi K2.6 with more NVIDIA Blackwell GPUs! Will be adding more in the coming days. Try it with OpenClaw: ollama launch openclaw -…

Scaling up Kimi K2.6 with more NVIDIA Blackwell GPUs! Will be adding more in the coming days. Try it with OpenClaw: ollama launch openclaw --model kimi-k2.6:cloud Try it with Hermes Agent: ollama laun

model-releasesollama--x

SCATR: Simple Calibrated Test-Time Ranking

arXiv:2604.16535v1 Announce Type: new Abstract: Test-time scaling (TTS) improves large language models (LLMs) by allocating additional compute at inference time. In practice, TTS is often achieved thr

researcharxiv-cs-lg

ScenarioControl: Vision-Language Controllable Vectorized Latent Scenario Generation

arXiv:2604.17147v1 Announce Type: new Abstract: We introduce ScenarioControl, the first vision-language control mechanism for learned driving scenario generation. Given a text prompt or an input image

researcharxiv-cs-cv

SciDraw-6K: A Multilingual Scientific Illustration Dataset Generated by Google Gemini

model-releasesarxiv-cs-cv

arXiv:2604.17206v1 Announce Type: new Abstract: We present SciDraw-6K, a curated dataset of 6,291 scientific illustrations synthesized by Google Gemini image-generation models, each paired with prompt

ScienceBoard: Evaluating Multimodal Autonomous Agents in Realistic Scientific Workflows

arXiv:2505.19897v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have extended their impact beyond Natural Language Processing, substantially fostering the development of interdi

SciImpact: A Multi-Dimensional, Multi-Field Benchmark for Scientific Impact Prediction

arXiv:2604.17141v1 Announce Type: new Abstract: The rapid growth of scientific literature calls for automated methods to assess and predict research impact. Prior work has largely focused on citation-