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Rethinking the Divergence Regularization in LLM RL

arXiv:2606.09821v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a key component of post-training large language models (LLMs). In practice, LLM RL is often off-policy because of

safetyarxiv-cs-lg

Retrieval Augmented Generation Framework for the Nepali Legal Domain Question Answering

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DGX agent

arXiv:2606.07523v1 Announce Type: cross Abstract: Legal domains in high-resource languages like English have widely adopted artificial intelligence for legal question answering. However, data scarcity

applicationsarxiv-cs-ai

9 Jun 2026

RetroReasoner: A Reasoning LLM for Strategic Retrosynthesis Prediction

arXiv:2603.12666v2 Announce Type: replace-cross Abstract: Retrosynthesis prediction aims to identify reactants that can synthesize a given product molecule. Although molecular large language models (L

Revisiting Articulated Parts Perception in Robot Manipulation

arXiv:2606.08103v1 Announce Type: cross Abstract: We are surrounded by various objects with movable, articulated parts, e.g., box, handle, door. An accurate and generalizable perception of articulated

safetyarxiv-cs-cv

Revisiting the shutdown problem

arXiv:2606.08296v1 Announce Type: new Abstract: A key premise in leading arguments for existential risk from artificial intelligence is that malfunctioning artificial agents could not be easily shut d

Revisiting Training Scale: An Empirical Study of Token Count, Power Consumption, and Parameter Efficiency

arXiv:2601.06649v2 Announce Type: replace-cross Abstract: Research in machine learning has questioned whether increases in training token counts reliably produce proportional performance gains in larg

Agents

Reward Evolution with Graph-of-Thoughts: A Bi-Level Language Model Framework for Reinforcement Learning

arXiv:2509.16136v5 Announce Type: replace Abstract: Designing effective reward functions remains a major challenge in reinforcement learning (RL), often requiring considerable human expertise and iter

agentsarxiv-cs-ro

Reward Shaping for (Inference-Time) Alignment: A Stackelberg Game Perspective

arXiv:2602.02572v2 Announce Type: replace-cross Abstract: Existing alignment methods directly use the reward model learned from user preference data to optimize an LLM policy, subject to KL regulariza

Rewrite to Translate, Translate to Reward: Reinforcement Learning for Source Rewriting in Machine Translation

arXiv:2606.08011v1 Announce Type: cross Abstract: Although directly prompting off-the-shelf Large Language Models (LLMs) to generate meaning-preserving source rewrites can effectively enhance Machine

Tutorials

RGB-S: Image-Aligned Tactile Saliency for Robust Dexterous Manipulation

arXiv:2606.08765v1 Announce Type: cross Abstract: Effective visuo-tactile integration is critical for robotic dexterous manipulation, especially when visual observations are unreliable or occluded. Ho

tutorialsarxiv-cs-cv

ridiculous oversimplification, from a prominent OpenAI employee no less. does this capture your impression of how the two companies have beh…

ridiculous oversimplification, from a prominent OpenAI employee no less. does this capture your impression of how the two companies have behaved? The OAI / Anthropic values difference is deeply misund

safetygary-marcus--x

RiskNet: A large-scale dataset of AI risk incidents from news with alignment and multi-dimensional annotations

arXiv:2606.08376v1 Announce Type: cross Abstract: As artificial intelligence (AI) systems are increasingly deployed across socially consequential domains, reports of AI-related harms and failures have

RLVE: Scaling Up Reinforcement Learning for Language Models with Adaptive Verifiable Environments

arXiv:2511.07317v2 Announce Type: replace-cross Abstract: We introduce Reinforcement Learning (RL) with Adaptive Verifiable Environments (RLVE), an approach using verifiable environments that procedur

safetyarxiv-cs-lg

Robot-DIFT: Correspondence-Sensitive Diffusion Features for Contact-Rich Robot Manipulation

arXiv:2602.11934v2 Announce Type: replace Abstract: Robot manipulation often fails in the final millimeters: a policy may recognize the right object yet miss the pose offsets, boundaries, or pre-conta

safetyarxiv-cs-ro

Robust In-Context Reinforcement Learning Under Reward Poisoning Attacks

arXiv:2506.06891v3 Announce Type: replace Abstract: We study the corruption-robustness of in-context reinforcement learning (ICRL), focusing on the Decision-Pretrained Transformer (DPT, Lee et al., 20

researcharxiv-cs-lg

Robust Random Graph Matching in Dense Graphs via an Approximate Message Passing Type Algorithm

arXiv:2412.16457v3 Announce Type: replace-cross Abstract: In this paper, we focus on the matching recovery problem between a pair of correlated Gaussian Wigner matrices with a latent vertex correspond

researcharxiv-cs-lg

Robust Renal Mass Segmentation on CT: A Validation Study of an AI-Based Framework

arXiv:2505.07573v2 Announce Type: replace-cross Abstract: Renal mass segmentation has important potential to enhance the clinical workflow, especially in settings requiring quantitative assessments. K

Robust-U1: Can MLLMs Self-Recover Corrupted Visual Content for Robust Understanding?

arXiv:2606.08063v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable success in visual understanding, yet their performance degrades significantly un

Rosetta Memory: Adaptive Memory for Cross-LLM Agents

arXiv:2606.07711v1 Announce Type: cross Abstract: Memory is the key component for transforming a stateless LLM into a persistent, evolving agent through experience accumulation, long-horizon planning,

Routine laboratory trajectories encode the onset of organ-level complications in cancer

arXiv:2606.08538v1 Announce Type: new Abstract: Routine laboratory panels drawn during cancer treatment constitute longitudinal physiological recordings of organ function, yet their temporal structure

applicationsarxiv-cs-lg

RPO-PDT: Demonstrating Role-Play-Based Knowledge Adaptation for Student Support Dialogue (Demonstration System)

arXiv:2606.09255v1 Announce Type: new Abstract: We present RPO-PDT: a retrieval-grounded, role-play-based dialogue system for adaptive student support in higher education. RPO-PDT is: (1) able to prov

safetyarxiv-cs-ro

RT-SDGOD: Real-Time Single-Domain Generalized Object Detection

arXiv:2606.09367v1 Announce Type: new Abstract: In real-world deployment under strict real-time constraints, weather and imaging variations induce significant distribution shifts, severely degrading d

applicationsarxiv-cs-cv

RTL-BenchLS: A Large-Scale Benchmark for RTL Reasoning and Generation with Large Language Models

arXiv:2606.08976v1 Announce Type: new Abstract: LLM-based RTL generation and reasoning is a promising direction for hardware design automation. High-quality benchmarks are critical infrastructure for

Rubrik turns its platform into an AI agent and ships Agent Cloud for Claude

model-releasessiliconangle

Rubrik Inc. today turned its data security platform into an autonomous agent and made its control layer for Anthropic PBC’s Claude generally available, the headline items in a wave of announcements at

Rule-based autocorrection of Piping and Instrumentation Diagrams (P&IDs) on graphs

arXiv:2502.18493v2 Announce Type: replace-cross Abstract: A piping and instrumentation diagram (P&ID) is a central reference document in chemical process engineering. Currently, chemical engineers man

applicationsarxiv-cs-ai

RunAgent SuperBrowser: A Theory of Autonomous Web Navigation Grounded in Human Browsing Behaviour

arXiv:2606.09399v1 Announce Type: new Abstract: We present SUPERBROWSER, an autonomous web-navigation agent designed against a single guiding hypothesis: a web agent should browse the way a person bro

SAD-Flower: Flow Matching for Safe, Admissible, and Dynamically Consistent Planning

arXiv:2511.05355v3 Announce Type: replace Abstract: Flow matching (FM) has shown promising results in data-driven planning. However, it inherently lacks formal guarantees for ensuring state and action

safetyarxiv-cs-lg

SAEExplainer: Interpreting SAE Features with Activation-Guided Preference Optimization

arXiv:2606.08496v1 Announce Type: cross Abstract: Although Sparse Autoencoders (SAEs) have mitigated the opacity of large language models (LLMs) by decomposing dense representations into sparse featur

researcharxiv-cs-lg

Safe, Fluent and Acceptable Motion Generation and Execution for Human--Robot Interaction in Manufacturing Environments

arXiv:2606.08741v1 Announce Type: new Abstract: Robots operating in human environments must not only ensure physical safety but also exhibit behaviors that are understandable, fluent, and acceptable t

safetyarxiv-cs-ro

Local Ai

Safe Polytope-in-Polytope Motion Planning and Control with Control Barrier Functions

arXiv:2606.09719v1 Announce Type: new Abstract: Autonomous mobile robots operating in tight environments require motion planning frameworks that account for the physical footprint of the robot. Simpli

local-aiarxiv-cs-ro

Safe-RULE: Safe Reinforcement UnLEarning

arXiv:2606.09559v1 Announce Type: cross Abstract: Offline safe reinforcement learning (Safe RL) enables policy learning without online interactions, making it suitable for safety-critical systems such

SafeECGMatch: Calibration-Aware Joint Frequency and Time Space Semi-Supervised Learning for Open-Set ECG Classification

arXiv:2606.08037v1 Announce Type: cross Abstract: Electrocardiogram (ECG) classification models often suffer from severe label scarcity, making semi-supervised learning (SSL) an attractive strategy fo

SafeRun: Enabling Determinism in LLM Planning for Running

arXiv:2606.09027v1 Announce Type: cross Abstract: Large Language Models enable flexible natural-language planning but remain unreliable in determinism-critical domains due to their probabilistic natur

Safety is Contextual, LLM-Judges Are Not: Navigating the Rigid Priors of Evaluators

arXiv:2606.07874v1 Announce Type: new Abstract: LLMs-as-judges are the only way to evaluate safety at scale. Despite their importance, LLM-judges themselves are rarely evaluated beyond human agreement

Agents

SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection

arXiv:2606.08146v1 Announce Type: new Abstract: Fraud detection in payment, e-commerce, and telecommunications systems requires accuracy at the individual level, robustness under severe class imbalanc

agentsarxiv-cs-ai

SAGE: Shape-Adapting Gated Experts for Adaptive Histopathology Image Segmentation

arXiv:2511.18493v4 Announce Type: replace-cross Abstract: The significant variability in cell size and shape continues to pose a major obstacle in computer-assisted cancer detection on gigapixel Whole

Industry

SailPoint shares fall despite earnings beat and raised guidance

Shares in SailPoint Inc. fell more than 11% today after the identity security company beat analyst expectations on revenue and adjusted earnings and raised its outlook, in a selloff that pointed to in

industrysiliconangle

Local Ai

SAILS: Surrogate-based Analysis of Interactions via Local Effect Smooths

arXiv:2606.09404v1 Announce Type: cross Abstract: Feature interactions drive much of the predictive power of machine learning models, yet existing explanation methods only detect and quantify interact

local-aiarxiv-cs-ai

Tutorials

Sample-Efficient LLM-Based Detection of Malicious Web Server Logs with Forensically Explainable Reasoning

arXiv:2606.08649v1 Announce Type: cross Abstract: Forensic analysis of web server logs demands both accurate detection and human-readable explanations that can satisfy legal requirements. We present C

tutorialsarxiv-cs-ai

Sample-Efficient Post-Training for LEGO Spatial-Physics Reasoning

arXiv:2606.07602v1 Announce Type: cross Abstract: LLM-based LEGO assembly generation requires both semantic grounding and physical feasibility. We identify a data-induced failure mode, PhysHack, in wh

SAW: Stage-Aware Dynamic Weighting for Multi-Objective Reinforcement Learning in Large Language Models

arXiv:2606.07705v1 Announce Type: cross Abstract: Although multi-objective reinforcement learning (MORL) is central to aligning large language models with complex human preferences, the prevailing pra

SC3: The Multi-Solvent Solubility Challenge and Benchmark

model-releasesarxiv-cs-lg

arXiv:2606.07656v1 Announce Type: cross Abstract: Solubility prediction is a standard benchmark in computational chemistry, yet multi-solvent models which reportedly approach the experimental-noise ce

Scaffold Effects on GAIA: A Controlled Comparison

arXiv:2606.08529v1 Announce Type: new Abstract: Published agent capability scores conflate what a model can do with what its scaffold lets it do, and the magnitude of this elicitation gap is not well

Hardware

Scale Robot Reinforcement Learning with NVIDIA Isaac Lab on Amazon SageMaker AI

In this post, we show how to train robot policies for the Unitree H1 humanoid with NVIDIA Isaac Lab on Amazon SageMaker AI across two compute options: Amazon SageMaker HyperPod and Amazon SageMaker Tr

hardwareaws-ml-blog

ScaleSweep: Accurate NVFP4 Post-Training Quantization of LLMs via Block Scale Initialization

arXiv:2606.07618v1 Announce Type: cross Abstract: NVFP4 is a recently introduced hardware-supported FP4 format that improves the fidelity of 4-bit quantization through fine-grained block scales. Howev

Scaling by Diversified Experience for Vision-Language-Action Models

model-releasesarxiv-cs-cv

arXiv:2606.09009v1 Announce Type: new Abstract: Vision-Language-Action models face significant challenges in real-world deployment due to the entanglement of high-level reasoning with low-level contro

Scaling Decision-Focused Learning to Large Problems with Lagrangian Decomposition

arXiv:2606.08797v1 Announce Type: cross Abstract: Decision-focused learning has shown great promise for addressing predict-then-optimize problems, particularly in the presence of under-specified model

Scaling Laws for Masked-Reconstruction Transformers on Single-Cell Transcriptomics

model-releasesarxiv-cs-lg

arXiv:2602.15253v2 Announce Type: replace Abstract: Neural scaling laws -- power-law relationships between loss, model size, and data -- have been extensively documented for language and vision transf