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Prosa: Rubric-Based Evaluation of LLMs on Real User Chats in Brazilian Portuguese

arXiv:2605.01630v1 Announce Type: new Abstract: Rankings produced by holistic LLM-as-a-judge scoring are sensitive to the bias of the chosen judge model. We show that switching to binary rubric scorin

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Safety

Protein-Conditioned Multi-Objective Reinforcement Learning for Full-Length mRNA Design

DGX agent

arXiv:2605.01513v1 Announce Type: new Abstract: Designing therapeutic messenger RNA (mRNA) requires creating full-length transcripts that carefully balance stability, translation efficiency, and immun

safetyarxiv-cs-lg

5 May 2026

ProtoFair: Fair Self-Supervised Contrastive Learning via Pseudo-Counterfactual Pairs

arXiv:2605.01971v1 Announce Type: new Abstract: Self-supervised learning methods learn high-quality visual representations, yet recent studies show that these representations often capture demographic

safetyarxiv-cs-cv

Proud of my analyst, Hermes This is what he has achieved after 1.5+ months of internship with me - Got me off X (doomscrolling cut from …

model-releasesnous-research--x

Proud of my analyst, Hermes This is what he has achieved after 1.5+ months of internship with me - Got me off X (doomscrolling cut from 2 hrs → 30 mins) - Practically paid for his salary via PMs b

Provable Benefit of Curriculum in Transformer Tree-Reasoning Post-Training

arXiv:2511.07372v3 Announce Type: replace Abstract: Recent curriculum techniques in the post-training stage of LLMs have been empirically observed to outperform non-curriculum approaches in improving

Tutorials

Provably Learning Attention with Queries

arXiv:2601.16873v2 Announce Type: replace Abstract: We study the problem of learning Transformer-based sequence models with black-box access to their outputs. In this setting, a learner may adaptively

tutorialsarxiv-cs-lg

Pruning Federated Models through Loss Landscape Analysis and Client Agreement Scoring

arXiv:2405.10271v4 Announce Type: replace Abstract: The practical deployment of Federated Learning (FL) on resource-constrained devices is fundamentally limited by the high cost of training large mode

Psychologically Potent, Computationally Invisible: LLMs Generate Social-Comparison Triggers They Fail to Detect

arXiv:2605.01017v1 Announce Type: new Abstract: We introduce Xiaohongshu Social Comparison Reader Elicitation (XHS-SCoRE), a reader-grounded benchmark for detecting if a text-only Xiaohongshu (RedNote

Public sector momentum and mission impact at Google Cloud Next ‘26

model-releasesgoogle-cloud-ai

The agentic era is here, and the public sector is at the forefront of leading this transformation.At Google Cloud Next ’26, it was clear that academia and public sector organizations are no longer jus

PubMed-Ophtha: An open resource for training ophthalmology vision-language models on scientific literature

arXiv:2605.02720v1 Announce Type: cross Abstract: Vision-language models hold considerable promise for ophthalmology, but their development depends on large-scale, high-quality image-text datasets tha

researcharxiv-cs-cl

PuppetAI: A Customizable Platform for Designing Tactile-Rich Affective Robot Interaction

arXiv:2602.04787v2 Announce Type: replace-cross Abstract: We introduce PuppetAI, a modular soft robot interaction platform. This platform offers a scalable cable-driven actuation system and a customiz

applicationsarxiv-cs-ro

Q-RAG: Long Context Multi-step Retrieval via Value-based Embedder Training

arXiv:2511.07328v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) methods enhance LLM performance by efficiently filtering relevant context for LLMs, reducing hallucinations and

QHyer: Q-conditioned Hybrid Attention-mamba Transformer for Offline Goal-conditioned RL

arXiv:2605.01862v1 Announce Type: new Abstract: Offline goal-conditioned RL (GCRL) learns goal-reaching policies from static datasets, but real-world datasets are often partially observable and histor

Hardware

Quant VideoGen: Auto-Regressive Long Video Generation via 2-Bit KV-Cache Quantization

arXiv:2602.02958v4 Announce Type: replace Abstract: Despite rapid progress in autoregressive video diffusion, an emerging system algorithm bottleneck limits both deployability and generation capabilit

hardwarearxiv-cs-lg

Quantifying and Predicting Disagreement in Graded Human Ratings

arXiv:2605.01168v1 Announce Type: new Abstract: It is increasingly recognized that human annotators do not always agree, and such disagreement is inherent in many annotation tasks. However, not all in

researcharxiv-cs-cl

Quantifying Multimodal Capabilities: Formal Generalization Guarantees in Pairwise Metric Learning

arXiv:2605.01424v1 Announce Type: new Abstract: Multimodal learning leverages the integration of diverse data modalities to enhance performance in complex tasks. Yet, it frequently encounters incomple

Quantum-centric supercomputing simulates 12,635-atom protein

IBM researchers demonstrated a quantum-centric supercomputing approach that successfully simulated a protein containing 12,635 atoms in collaboration with Cleveland Clinic and RIKEN, combining classic

researchibm-research

Quantum-inspired Techniques in Tensor Networks for Industrial Contexts

arXiv:2404.11277v2 Announce Type: replace-cross Abstract: In this paper we present a study of the applicability and feasibility of quantum-inspired algorithms and techniques in tensor networks for ind

Industry

QuantWare raises $178M to become the TSMC of quantum computing

Netherlands-based quantum computing hardware company QuantWare B.V. said today it has raised 178 million in funding to accelerate its plans of creating an “open architecture” for the industry. The rou

industrysiliconangle

Quasi-Static Control of Discrete Cosserat Rod

arXiv:2605.01395v1 Announce Type: cross Abstract: In this paper, we design feedback control laws for soft robots modelled using the Cosserat rod, which is spatially discretised using the Piecewise Con

researcharxiv-cs-ro

Quaternion Nonlinear Transform-Induced Nuclear Norm for Low-Rank Tensor Completion

model-releasesarxiv-cs-cv

arXiv:2605.01467v1 Announce Type: cross Abstract: Tensor completion has emerged as a powerful framework for recovering missing data in multidimensional signals by exploiting low-rank tensor structures

Tools

Query observability metrics using the Vercel CLI

The Vercel CLI now includes functionality to query and monitor observability metrics directly from the command line, allowing developers to inspect performance data without leaving their terminal envi

toolsvercel-blog

RA-CMF: Region-Adaptive Conditional MeanFlow for CT Image Reconstruction

arXiv:2605.00901v1 Announce Type: new Abstract: The use of CT imaging is important for screening, diagnosis, therapy planning, and prognosis of lung cancers. Unfortunately, due to differences in imagi

safetyarxiv-cs-cv

RADMI: Latent Information Aggregation as a Proxy for Model Uncertainty

model-releasesarxiv-cs-cv

arXiv:2605.01502v1 Announce Type: new Abstract: Epistemic uncertainty estimation is essential for identifying regions where deep learning system outputs may be unreliable. However, existing approaches

RAFNet: Region-Aware Fusion Network for Pansharpening

model-releasesarxiv-cs-cv

arXiv:2605.02184v1 Announce Type: new Abstract: Pansharpening aims to generate high-resolution multispectral (HRMS) images by fusing low-resolution multispectral (LRMS) and high-resolution panchromati

RamanBench: A Large-Scale Benchmark for Machine Learning on Raman Spectroscopy

arXiv:2605.02003v1 Announce Type: new Abstract: Machine Learning (ML) has transformed many scientific fields, yet key applications still lack standardized benchmarks. Raman spectroscopy, a widely used

Random-Effects Algorithm for Random Objects in Metric Spaces

arXiv:2605.02693v1 Announce Type: cross Abstract: Across many scientific disciplines, multiple observations are collected from the same experimental units, and in modern datasets these observations of

RAST-MoE-RL: A Regime-Aware Spatio-Temporal MoE Framework for Deep Reinforcement Learning in Ride-Hailing

arXiv:2512.13727v2 Announce Type: replace Abstract: Ride-hailing platforms face the challenge of balancing passenger waiting times with overall system efficiency under highly uncertain supply-demand c

Rate-optimal Design for Anytime Best Arm Identification

arXiv:2510.23199v3 Announce Type: replace-cross Abstract: We consider the best arm identification problem, where the goal is to identify the arm with the highest mean reward from a set of K arms under

Rationality Measurement and Theory for Reinforcement Learning Agents

arXiv:2602.04737v2 Announce Type: replace Abstract: This paper proposes a suite of rationality measures and associated theory for reinforcement learning agents, a property increasingly critical yet ra

safetyarxiv-cs-lg

Real-Time Text Transmission via LLM-Based Entropy Coding over Fixed-Rate Channels

arXiv:2605.01991v1 Announce Type: cross Abstract: Learning, prediction, and compression are intimately connected: a model that accurately predicts the next symbol in a sequence can be coupled with a s

Recall to Predict: Grounding Motion Forecasting in Interpretable Motion Bank

arXiv:2605.01393v1 Announce Type: new Abstract: Motion forecasting often requires trading interpretability for predictive accuracy. Standard anchor-based architectures rely on opaque latent queries th

Tutorials

RECAP: An End-to-End Platform for Capturing, Replaying, and Analyzing AI-Assisted Programming Interactions

arXiv:2605.01104v1 Announce Type: cross Abstract: Understanding how developers interact with AI coding assistants requires more than chat logs or git histories in isolation; it requires reconstructing

tutorialsarxiv-cs-cl

RECAP: Transparent Inference-Time Emotion Alignment for Medical Dialogue Systems

arXiv:2509.10746v3 Announce Type: replace Abstract: Large language models in healthcare often produce emotionally flat or opaque responses, failing to provide the transparent reasoning required for cl

safetyarxiv-cs-cl

Reconstructing conformal field theoretical compositions with Transformers

arXiv:2605.01072v1 Announce Type: cross Abstract: We study the use of transformers to reconstruct the compositions of tensor products of two-dimensional rational conformal field theories (RCFTs) based

Reconstruction Interval Z-Phase Dependence of AI Detection Sensitivity in CT Lung Nodule Screening

arXiv:2605.00971v1 Announce Type: cross Abstract: Background: Sensitivity of AI-assisted lung nodule detection systems is known to vary with CT acquisition parameters including radiation dose, reconst

Recurrent Deep Reinforcement Learning for Chemotherapy Control under Partial Observability

arXiv:2605.02552v1 Announce Type: new Abstract: Chemotherapy dose optimization can be formulated as a dynamic treatment regime, requiring sequential decisions under uncertainty that must balance tumor

Recurrent Graph Neural Networks and Arithmetic Circuits

arXiv:2603.05140v2 Announce Type: replace-cross Abstract: We characterise the computational power of recurrent graph neural networks (GNNs) in terms of arithmetic circuits over the real numbers. Our n

Tutorials

.@Redisinc is returning to Interrupt! Say hello to their team at the expo hall to learn about their fast memory layer for chatbots and AI ag…

tutorialsharrison-chase--x

.@Redisinc is returning to Interrupt! Say hello to their team at the expo hall to learn about their fast memory layer for chatbots and AI agents as well as their ready-to-use tools for building AI app

Reference-Sampled Boltzmann Projection for KL-Regularized RLVR: Target-Matched Weighted SFT, Finite One-Shot Gaps, and Policy Mirror Descent

arXiv:2605.02469v1 Announce Type: new Abstract: Online reinforcement learning with verifiable rewards (RLVR) turns checkable outcomes into a scalable training signal, but it keeps rollout generation,

Referring Multiple Regions with Large Multimodal Models via Contextual Latent Steering

arXiv:2605.01827v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) have recently demonstrated their proficiency in holistic visual comprehension. However, most of them struggle to tackle r

Refracting Reality: Generating Images with Realistic Transparent Objects

arXiv:2511.17340v3 Announce Type: replace Abstract: Generative image models can produce convincingly real images, with plausible shapes, textures, layouts and lighting. However, one domain in which th

ReFRAME or Remain: Unsupervised Lexical Semantic Change Detection with Frame Semantics

arXiv:2602.04514v3 Announce Type: replace Abstract: The majority of contemporary computational methods for lexical semantic change (LSC) detection are based on neural embedding distributional represen

researcharxiv-cs-cl

RefusalGuard: Geometry-Preserving Fine-Tuning for Safety in LLMs

arXiv:2605.01913v1 Announce Type: cross Abstract: Fine-tuning safety-aligned language models for downstream tasks often leads to substantial degradation of refusal behavior, making models vulnerable t

Registration-Free Learnable Multi-View Capture of Faces in Dense Semantic Correspondence

arXiv:2605.01450v1 Announce Type: new Abstract: Recent frameworks like ToFu and TEMPEH provide an automated alternative to classical registration pipelines by predicting 3D meshes in dense semantic co

safetyarxiv-cs-cv

Reinforcement Learning for LLM-based Multi-Agent Systems through Orchestration Traces

arXiv:2605.02801v1 Announce Type: new Abstract: As large language model (LLM) agents evolve from isolated tool users into coordinated teams, reinforcement learning (RL) must optimize not only individu

Reinforcement Learning from Compiler and Language Server Feedback

arXiv:2510.22907v2 Announce Type: replace Abstract: Coding agents fail when text-level guesses outrun program facts: they hallucinate APIs, drift to the wrong symbol, and apply edits without evidence

safetyarxiv-cs-cl

Reliability-Oriented Multilingual Orthopedic Diagnosis: A Domain-Adaptive Modeling and a Conceptual Validation Framework

arXiv:2605.02266v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly proposed for clinical decision support including multilingual diagnosis in low-resource settings. However,

safetyarxiv-cs-cl