All entries

Reason Twice: Segmentation via Candidate Discovery and Comparative Reasoning

model-releasesarxiv-cs-cv

arXiv:2606.09303v1 Announce Type: new Abstract: The rapid development of pretrained foundation models has enabled more general image segmentation. Multimodal large language models (MLLMs) have been wi

Reasoning Arena: Trace Tournaments When Verifiable Rewards Fall Short

DGX agent

arXiv:2606.09380v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a leading paradigm for improving the reasoning ability of large language models throu

researcharxiv-cs-ai

9 Jun 2026

Reconstructing and forecasting disease trajectories of patients with Alzheimer's disease using routine data in resource-constrained settings

arXiv:2606.07798v1 Announce Type: new Abstract: Alzheimer's disease is a progressive neurodegenerative disorder, and its progression varies substantially across patients. Existing work aims to forecas

Reconstructing Synthetic SDO/AIA 193 A EUV Images from He I 10830 A Observations with Diffusion Model Translator

arXiv:2606.08652v1 Announce Type: cross Abstract: Routine full-disk EUV imaging has been available only since the modern era, such as SOHO and SDO. To extend EUV coronal context into earlier periods,

ReCoVLA: VLM-Guided Reward Compilation for Failure Recovery in Vision-Language-Action Policies

arXiv:2606.09630v1 Announce Type: cross Abstract: Vision-language-action (VLA) policies provide strong priors for language-conditioned manipulation, but remain brittle in off-nominal states requiring

RecurGuard: Runtime Monitoring for Reasoning-Token Consumption Attacks

arXiv:2606.07968v1 Announce Type: cross Abstract: Reasoning-capable large language models can be induced to spend their generation budget on injected decoy tasks rather than answering the user's quest

REFINE: Super-efficient 3D Gaussian Splatting Pruning via Rendering-Free Primitive Importance

model-releasesarxiv-cs-cv

arXiv:2606.09074v1 Announce Type: new Abstract: Existing pruning methods for 3D Gaussian splatting (3DGS) suffer from either severe quality degradation or prohibitive computational overhead. In this p

REFLECT: Intervention-Supported Error Attribution for Silent Failures in LLM Agent Traces

arXiv:2606.09071v1 Announce Type: new Abstract: Large language model (LLM) agents now solve complex tasks through long plan-and-execution traces, yet the ability to locate errors in a completed traces

agentsarxiv-cs-ai

Reflection in the Dark: Exposing and Escaping the Black Box in Reflective Prompt Optimization

arXiv:2603.18388v2 Announce Type: replace Abstract: Automatic prompt optimization (APO) has emerged as a powerful paradigm for improving LLM performance without manual prompt engineering. Reflective A

agentsarxiv-cs-ai

Reformulate LLM Reinforcement Learning for Efficient Training under Black-box Discrepancy

model-releasesarxiv-cs-lg

arXiv:2606.08779v1 Announce Type: new Abstract: Reinforcement Learning (RL) has emerged as a pivotal post-training paradigm, yet it frequently suffers from unpredictable sub-optimum performance or eve

ReGIL: Retrieval-Guided Imitation Learning from a Single Demonstration

arXiv:2606.09381v1 Announce Type: new Abstract: Learning robot manipulation policies with deep neural networks from a single demonstration remains highly challenging, as even small deviations from the

safetyarxiv-cs-ro

Region-Wise Correspondence Prediction between Manga Line Art Images

arXiv:2509.09501v4 Announce Type: replace Abstract: Understanding region-wise correspondences between manga line art images is fundamental for high-level manga processing, supporting downstream tasks

safetyarxiv-cs-cv

Reinforcement Learning for Flow-Matching Policies with Density Transport

arXiv:2606.08602v1 Announce Type: cross Abstract: We present an online reinforcement learning (RL) algorithm for fine-tuning flow-matching policies in continuous-control problems. Our key insight is t

Reinforcement learning in linear embedding space unlocks generalizable control across soft robot configurations

arXiv:2606.08104v1 Announce Type: new Abstract: Soft-bodied organisms such as octopuses and elephant trunks exhibit remarkable morphological adaptability, dynamically reconfiguring body shape and stif

safetyarxiv-cs-ro

Reinforcing Temporal Answer Grounding in Instructional Video via Candidate-Aware Causal Reasoning

arXiv:2606.08436v1 Announce Type: new Abstract: The task of temporal answer grounding in instructional video (TAGV), which aims to locate precise video segments that respond to natural language querie

safetyarxiv-cs-cv

Local Ai

Relational Epipolar Graphs for Robust Relative Camera Pose Estimation

arXiv:2604.04554v2 Announce Type: replace Abstract: A key component of Visual Simultaneous Localization and Mapping (VSLAM) is estimating relative camera poses using matched keypoints. Accurate estima

local-aiarxiv-cs-cv

Reliable to Expressive: A Curriculum for Rubric-Following Safety Judges

arXiv:2606.09165v1 Announce Type: new Abstract: Safety judges are increasingly deployed to evaluate model outputs against evolving criteria, yet recent meta-evaluation work shows they remain brittle u

Remember with Confidence: Uncertainty Quantification for Spatio-temporal Memory with Probabilistic Guarantees

model-releasesarxiv-cs-cv

arXiv:2606.08277v1 Announce Type: new Abstract: Long-horizon robot operation requires spatio-temporal memory to record the environment state and recall it for downstream reasoning. Scene graphs and re

Reminder: The only place to download the Hermes Agent Desktop App is https://hermes-agent.nousresearch.com/desktop Any other website or sour…

Reminder: The only place to download the Hermes Agent Desktop App is https://hermes-agent.nousresearch.com/desktop Any other website or source is dangerous and could contain old, or worse, dangerous a

agentsnous-research--x

Industry

Rental screening startup 100 acquires fraud detection firm Cobblestone Labs

Rental screening startup 100 today announced that it has acquired Cobblestone Labs Inc., a fraud detection and income verification platform built by former engineers from corporate card company Ramp B

industrysiliconangle

Repair Before Veto, When Repair Is Hidden: Quantum-Accessible Features for Repair-Augmented Constraint Learning

arXiv:2606.08020v1 Announce Type: cross Abstract: Hard-constraint decision systems usually veto infeasible candidates. This is too rigid when the system can act: if a known affordable repair would mak

Repetition Mismatch: Why Data Mixture Experiments Don't Scale and How to Fix Them

arXiv:2606.07597v1 Announce Type: cross Abstract: Pre-training data mixtures are commonly tuned by running small-scale experiments and extrapolating to the target training budget. When high-quality da

RepoLaunch: Automating Build and Management of Code Repositories across Languages and Platforms

arXiv:2603.05026v2 Announce Type: replace-cross Abstract: Language model (LM) agents have driven substantial progress in automated software engineering (SWE), yet building and testing software reposit

agentsarxiv-cs-lg

Report: GKE Inference Gateway delivers up to 92% faster AI responses

model-releasesgoogle-cloud-ai

As generative AI moves from experimental pilots to massive production environments, the efficiency of your infrastructure becomes the ultimate differentiator. One way to get the most out of it and min

Report on CHIIR 2026 Workshop on Generative AI and Academic Search (GAI&AS)

arXiv:2606.08936v1 Announce Type: cross Abstract: This report summarizes the CHIIR 2026 Workshop on Generative AI and Academic Search (GAI&AS), which examined how GenAI is reshaping academic search sy

Report the Floor: A Training-Free Conformal Interval Is a Mandatory Baseline for Probabilistic Time-Series Forecasting

arXiv:2606.09473v1 Announce Type: cross Abstract: Probabilistic forecasters are increasingly learned, yet the baselines they are compared against are often weak or omitted. We show that the simplest p

researcharxiv-cs-lg

ResearchClawBench: A Benchmark for End-to-End Autonomous Scientific Research

arXiv:2606.07591v1 Announce Type: cross Abstract: AI coding agents are increasingly used for scientific work, but their end-to-end autonomous research capability remains difficult to verify. We presen

Hardware

Resource-aware Computation-Communication Overlap for multi-GPU ML Workloads

arXiv:2606.09200v1 Announce Type: cross Abstract: The rapid growth of large-scale machine learning (ML) has made distributed training across multiple GPUs a fundamental component of modern ML systems.

hardwarearxiv-cs-ai

Tutorials

ReTabSyn: Realistic Tabular Data Synthesis via Reinforcement Learning

arXiv:2603.10823v2 Announce Type: replace-cross Abstract: Deep generative models can help with data scarcity and privacy by producing synthetic training data, but they struggle in low-data, imbalanced

tutorialsarxiv-cs-lg

Rethinking 3D Shape Generation: Diffusion over Superquadrics

arXiv:2606.08957v1 Announce Type: new Abstract: Diffusion models have advanced 3D shape generation, yet most methods still denoise in high-cardinality spaces (e.g., voxel/SDF grids, meshes, or point c

researcharxiv-cs-cv

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

Applications

Retrieval Augmented Generation Framework for the Nepali Legal Domain Question Answering

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

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

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