model releases

MTR-Suite: A Framework for Evaluating and Synthesizing Conversational Retrieval Benchmarks

arXiv:2605.20729v1 Announce Type: new Abstract: Accurate evaluation of conversational retrieval is pivotal for advancing Retrieval-Augmented Generation (RAG) systems. However, existing conversational

Model Releases

Multimodal Optimal Transport for Training-free Temporal Segmentation in Surgical Robotics

DGX agent

arXiv:2602.24138v2 Announce Type: replace Abstract: Automated recognition of surgical phases and steps is a fundamental capability for intraoperative decision support, workflow automation, and skill a

model-releasesarxiv-cs-cv

21 May 2026

Neural Negative Binomial Regression for Weekly Seismicity Forecasting: Per-Cell Dispersion Estimation and Tail Risk Assessment

arXiv:2605.21437v1 Announce Type: cross Abstract: Standard approaches to forecasting the weekly number of earthquakes on a spatial grid rely on the Poisson distribution with a single global dispersion

NeuroQA: A Large-Scale Image-Grounded Benchmark for 3D Brain MRI Understanding

arXiv:2605.20525v1 Announce Type: cross Abstract: We present NeuroQA, a large-scale benchmark for visual question answering in 3D brain magnetic resonance imaging (MRI), with 56,953 QA pairs from 12,9

New inflection point in the accelerating growth of open-source models usage is coming

model-releasesclem-delangue--x

New inflection point in the accelerating growth of open-source models usage is coming 🦔Microsoft canceled its internal Claude Code licenses this week after token-based billing made the cost untenable,

Nonparametric Learning and Earning with One-Point Feedback under Nonstationarity

arXiv:2605.21263v1 Announce Type: new Abstract: Firms increasingly rely on dynamic pricing to respond to evolving customer demand, yet in many applications they observe only the revenue generated by a

On Evals - getting messages on “ok so how do I actually start learning this?” there is no better way than by just doing so you can copy this…

model-releasesharrison-chase--x

On Evals - getting messages on “ok so how do I actually start learning this?” there is no better way than by just doing so you can copy this to Claude Code and get started today <instructions> 1. Go l

On the limits and opportunities of AI reviewers: Reviewing the reviews of Nature-family papers with 45 expert scientists

arXiv:2605.20668v1 Announce Type: new Abstract: With the advancement of AI capabilities, AI reviewers are beginning to be deployed in scientific peer review, yet their capability and credibility remai

On the Suboptimality of GP-UCB under Polynomial Effective Optimism

arXiv:2312.01386v2 Announce Type: replace Abstract: Gaussian process upper confidence bound (GP-UCB) is widely used for sequential optimization of expensive black-box functions. Although many upper bo

Open source 🤝 NVIDIA

Open source 🤝 NVIDIA 👏 Congratulations to @cohere on Command A+ — a powerful new model optimized for NVIDIA Blackwell and trained using NVIDIA CUDA-X libraries. Proud to be a part of it! Learn more ⤵️

model-releasescohere--x

Optimization Hyper-parameter Laws for Large Language Models

arXiv:2409.04777v4 Announce Type: replace Abstract: Large Language Models have driven significant AI advancements, yet their training is resource-intensive and highly sensitive to hyper-parameter sele

Parameters as Experts: Adapting Vision Models with Dynamic Parameter Routing

arXiv:2602.06862v2 Announce Type: replace Abstract: Adapting pre-trained vision models using parameter-efficient fine-tuning (PEFT) remains challenging, as it aims to achieve performance comparable to

PGC: Peak-Guided Calibration for Generalizable AI-Generated Image Detection

arXiv:2605.21207v1 Announce Type: new Abstract: The rapid evolution of generative AI, from GANs to modern diffusion models, has resulted in increasingly subtle discriminative clues. These fine-grained

PlanningBench: Generating Scalable and Verifiable Planning Data for Evaluating and Training Large Language Models

arXiv:2605.20873v1 Announce Type: cross Abstract: Planning is a fundamental capability for large language models (LLMs) because such complex tasks require models to coordinate goals, constraints, reso

Point Cloud Sequence Encoding for Material-conditioned Graph Network Simulators

arXiv:2605.20978v1 Announce Type: new Abstract: Graph Network Simulators (GNSs) have emerged as powerful surrogates for complex physics-based simulation, offering inherent differentiability and orders

Post-Hoc Understanding of Metaphor Processing in Decoder-Only Language Models via Conditional Scale Entropy

arXiv:2605.21391v1 Announce Type: new Abstract: Metaphor requires a language model to resolve a token whose contextual meaning diverges from its basic literal sense. Understanding how transformer mode

Preserve, Reveal, Expand: Faithful 4D Video Editing with Region-Aware Conditioning

arXiv:2605.20961v1 Announce Type: new Abstract: Existing 4D-driven video diffusion models primarily target plausible generation, but faithful 4D editing requires preserving source-observed regions whi

proof too complicated, Claude help ELI5

model-releasesjerry-liu--x

proof too complicated, Claude help ELI5 Today, we share a breakthrough on the planar unit distance problem, a famous open question first posed by Paul Erdős in 1946. For nearly 80 years, mathematician

Pseudo-Formalization for Automatic Proof Verification

arXiv:2605.20531v1 Announce Type: cross Abstract: Reliable verification of proofs remains a bottleneck for training and evaluating AI systems on hard mathematical reasoning. Fully formal proofs, in la

Q-DiT4SR: Exploration of Detail-Preserving Diffusion Transformer Quantization for Real-World Image Super-Resolution

arXiv:2602.01273v4 Announce Type: replace Abstract: Recently, Diffusion Transformers (DiTs) have emerged in Real-World Image Super-Resolution (Real-ISR) to generate high-quality textures, yet their he

Quantifying Hyperparameter Transfer and the Importance of Embedding Layer Learning Rate

arXiv:2605.21486v1 Announce Type: new Abstract: Hyperparameter transfer allows extrapolating optimal optimization hyperparameters from small to large scales, making it critical for training large lang

Quantum reservoir computing in Jaynes-Cummings models: Nonlinear memory and time-series prediction

arXiv:2510.00171v2 Announce Type: replace-cross Abstract: We investigate quantum reservoir computing (QRC) using a hybrid qubit-boson system described by the Jaynes-Cummings (JC) Hamiltonian and its d

Query-Calibrated Segmental Admission for Descriptor-Agnostic LiDAR Loop Closure in Repetitive Environments

arXiv:2512.09447v2 Announce Type: replace-cross Abstract: Structurally repetitive environments produce visually plausible but aliased LiDAR loop candidates that can destabilize pose-graph optimization

Qwen 3.7 Max now available on Vercel AI Gateway

model-releasesvercel-blog

Vercel has announced the availability of Qwen 3.7 Max, a language model, through its Vercel AI Gateway platform. This integration allows developers to access and use Qwen 3.7 Max alongside other AI mo

QwenSafe: Multimodal Content Rating Description Identification via Preference-Aligned VLMs

arXiv:2605.20584v1 Announce Type: new Abstract: Mobile app marketplaces require developers to disclose standardized content rating descriptors (CRDs) to inform users about potentially sensitive or res

RadProPoser: Probabilistic Radar Tensor Human Pose Estimation That Knows Its Limits

arXiv:2508.03578v2 Announce Type: replace Abstract: Radar-based human pose estimation enables privacy-preserving motion tracking for ambient intelligence, yet the noisy nature of radar sensing makes u

RankE: End-to-End Post-Training for Discrete Text-to-Image Generation with Decoder Co-Evolution

arXiv:2605.21195v1 Announce Type: new Abstract: Discrete autoregressive (AR) text-to-image (T2I) models pair a VQ tokenizer with an AR policy, and current post-training pipelines optimize only the pol

RCGDet3D: Rethinking 4D Radar-Camera Fusion-based 3D Object Detection with Enhanced Radar Feature Encoding

arXiv:2605.21112v1 Announce Type: new Abstract: 4D automotive radar is indispensable for autonomous driving due to its low cost and robustness, yet its point cloud sparsity challenges 3D object detect

Refining and Reusing Annotation Guidelines for LLM Annotation

arXiv:2605.20809v1 Announce Type: new Abstract: While Large Language Models (LLMs) demonstrate remarkable performance on zero-shot annotation tasks, they often struggle with the specialized convention

Reinforcing Human Behavior Simulation via Verbal Feedback

arXiv:2605.20506v1 Announce Type: cross Abstract: Humans learn social norms and behaviors from verbal feedback (e.g., a parent saying 'that was rude' or a friend explaining 'here's why that hurt'). Ye

Residual Paving: Diagnosing the Routing Bottleneck in Selective Refusal Editing

arXiv:2605.20262v1 Announce Type: new Abstract: We study selective refusal editing as a three-way control problem: induce non-refusal on designated edit prompts while preserving benign behavior and ha

Resolving Long-Tail Ambiguity in Unsupervised 3D Point Cloud Segmentation with Language Priors

arXiv:2605.20737v1 Announce Type: new Abstract: Existing approaches for unsupervised 3D point cloud segmentation predominantly rely on a purely visual similarity-based learning-by-clustering paradigm,

Retrieval-Augmented Long-Context Translation for Cultural Image Captioning: Gators submission for AmericasNLP 2026 shared task

arXiv:2605.20626v1 Announce Type: new Abstract: We present the University of Florida Gators submission to the AmericasNLP 2026 shared task on cultural image captioning for Indigenous languages. Our tw

Robust Personalized Recommendation under Hidden Confounding in MNAR

arXiv:2605.21066v1 Announce Type: new Abstract: Recommender systems often rely on observational user--item interaction data, which is prone to selection bias due to users' selective interactions with

roto 2.0: The Robot Tactile Olympiad

arXiv:2605.21429v1 Announce Type: cross Abstract: Tactile-based reinforcement learning (RL) is currently hindered by fragmented research and a focus on over-saturated orientation tasks. We introduce v

Runtime-Certified Bounded-Error Quantized Attention

arXiv:2605.20868v1 Announce Type: new Abstract: KV cache quantization reduces the memory cost of long-context LLM inference, but introduces approximation error that is typically validated only empiric

Safety-Critical Control for Smoothed Implicit Contact Dynamics

model-releasesarxiv-cs-ro

arXiv:2605.21138v1 Announce Type: new Abstract: Smoothed implicit contact dynamics enables gradient-based planning and control for contact-rich tasks without predefined mode sequences. However, safety

Seeing Through Fog: Towards Fog-Invariant Action Recognition

arXiv:2605.20645v1 Announce Type: new Abstract: Foggy conditions are commonly encountered in real-world applications; however, existing action recognition approaches typically assume favorable weather

Seems GPT-5.2 reaches expert level in peer review: 45 scientists took 469 hours evaluating human & AI reviews on 82 papers. 'Surprisingly, c…

model-releasesethan-mollick--x

Seems GPT-5.2 reaches expert level in peer review: 45 scientists took 469 hours evaluating human & AI reviews on 82 papers. 'Surprisingly, current AI reviewers are competitive even with the top-rated

Self-Evolving in the Wild：Over the course of ~35 hours of continuous autonomous execution, the model performed 432 kernel evaluations across…

Self-Evolving in the Wild：Over the course of ~35 hours of continuous autonomous execution, the model performed 432 kernel evaluations across 1,158 tool calls. It wrote, compiled, profiled, and iterati

model-releasesqwen--x

Semiparametric Efficient Bilevel Gradient Estimation

arXiv:2605.21341v1 Announce Type: cross Abstract: Functional bilevel methods estimate a lower-level function and plug it into a hypergradient, but this plug-in gradient can retain first-order bias whe

Sequential Data Augmentation for Generative Recommendation

arXiv:2509.13648v3 Announce Type: replace Abstract: Generative recommendation plays a crucial role in personalized systems, predicting users' future interactions from their historical behavior sequenc

ShadeBench: A Benchmark Dataset for Building Shade Simulation in Sustainable Society

arXiv:2605.20510v1 Announce Type: new Abstract: Urban heat exposure is becoming an increasingly critical challenge due to the intensifying urban heat island effect. Fine-grained shade patterns, especi

ShapeBench: A Scalable Benchmark and Diagnostic Suite for Standardized Evaluation in Aerodynamic Shape Optimization

arXiv:2605.20763v1 Announce Type: new Abstract: Rapid progress in aerodynamic shape optimization (ASO) has outpaced currently-available standardized evaluation frameworks. Fair comparison requires a u

SHINE: A Scalable In-Context Hypernetwork for Mapping Context to LoRA in a Single Pass

arXiv:2602.06358v2 Announce Type: replace Abstract: We propose SHINE (Scalable Hyper In-context NEtwork), a scalable hypernetwork that can map diverse meaningful contexts into high-quality LoRA adapte

SMoA: Spectrum Modulation Adapter for Parameter-Efficient Fine-Tuning

arXiv:2605.21147v1 Announce Type: cross Abstract: As the number of model parameters increases, parameter-efficient fine-tuning (PEFT) has become the go-to choice for tailoring pre-trained large langua

SOLAR: A Self-Optimizing Open-Ended Autonomous Agent for Lifelong Learning and Continual Adaptation

arXiv:2605.20189v1 Announce Type: cross Abstract: Despite the remarkable success of large language models (LLMs), they still face bottlenecks while deploying in dynamic, real-world settings with prima

SOPE: Stabilizing Off-Policy Evaluation for Online RL with Prior Data

arXiv:2605.05863v2 Announce Type: replace Abstract: Incorporating prior data into online reinforcement learning accelerates training but typically forces a difficult trade-off between high computation