Search: “model-releases”

PBT-Bench: Benchmarking AI Agents on Property-Based Testing

arXiv:2605.15229v1 Announce Type: cross Abstract: Existing code benchmarks measure whether an agent can produce any test that reproduces a known bug, or whether it can produce a patch that fixes a des

Model Releases

PDRNN: Modular Data-driven Pedestrian Dead Reckoning on Loosely Coupled Radio- and Inertial-Signalstreams

DGX agent

arXiv:2605.15252v1 Announce Type: cross Abstract: Modern pedestrian dead reckoning (PDR) systems rely on fusing noisy and biased estimates of position, velocity, and calibrated orientation derived fro

model-releasesarxiv-cs-ai

18 May 2026

PerfCodeBench: Benchmarking LLMs for System-Level High-Performance Code Optimization

arXiv:2605.15222v1 Announce Type: cross Abstract: Large language models (LLMs) can often generate functionally correct code, but their ability to produce efficient implementations for performance-crit

Perforated Neural Networks for Keyword Spotting

arXiv:2605.15647v1 Announce Type: new Abstract: Edge machine learning presents a unique set of constraints not encountered in cloud-scale model deployment: strict memory budgets, limited compute, and

PhyDetEx: Detecting and Explaining the Physical Plausibility of T2V Models

arXiv:2512.01843v2 Announce Type: replace Abstract: Driven by the growing capacity and training scale, Text-to-Video (T2V) generation models have recently achieved substantial progress in video qualit

Position: Early-Stage Quality Assurance in Annotation Pipelines Is More Cost-Effective Than Late-Stage Validation

arXiv:2605.15714v1 Announce Type: cross Abstract: This position paper argues that the machine learning community should prioritize early-stage quality assurance in annotation pipelines over the prevai

Position: Ideas Should be the Center of Machine Learning Research

arXiv:2605.15253v1 Announce Type: new Abstract: Machine learning research increasingly bifurcates into two disconnected modes: benchmark-driven engineering that prioritizes metrics over understanding,

Probabilistic Dating of Historical Manuscripts via Evidential Deep Regression on Visual Script Features

arXiv:2605.06475v1 Announce Type: cross Abstract: We introduce a probabilistic approach for dating historical manuscript pages from visual features alone. Instead of aggregating centuries into classes

Prompting Amazon Nova 2 for content moderation

model-releasesaws-ml-blog

In this post, you learn how to prompt Amazon Nova 2 Lite for content moderation using structured and free-form approaches, grounded in the MLCommons AILuminate Assessment Standard. The prompting techn

Quantization Undoes Alignment: Bias Emergence in Compressed LLMs Across Models and Precision Levels

arXiv:2605.15208v1 Announce Type: cross Abstract: Large Language Models are routinely compressed via post-training quantization to reduce inference costs and memory footprint for cloud and edge deploy

Quantum Feature Pyramid Gating for Seismic Image Segmentation

arXiv:2605.15370v1 Announce Type: cross Abstract: Accurate salt-body delineation is essential for seismic interpretation because salt structures distort wave propagation, complicate velocity-model bui

🚀🚀Qwen3.7 Preview lands on Arena ！ Here come Qwen3.7-Max-Preview & Qwen3.7-Plus-Preview. Alibaba now #6 lab in Text, #5 in Vision.⚡️⚡️ Can…

🚀🚀Qwen3.7 Preview lands on Arena ！ Here come Qwen3.7-Max-Preview & Qwen3.7-Plus-Preview. Alibaba now #6 lab in Text, #5 in Vision.⚡️⚡️ Can't wait to release Qwen3.7 series models！Stay tuned! @arena Qw

model-releasesqwen--x

RapidUn: Influence-Driven Parameter Reweighting for Efficient Large Language Model Unlearning

arXiv:2512.04457v2 Announce Type: replace Abstract: Removing specific data influence from large language models (LLMs) remains challenging, as retraining is costly and existing approximate unlearning

RAR: Retrieving And Ranking Augmented MLLMs for Visual Recognition

arXiv:2403.13805v2 Announce Type: replace-cross Abstract: CLIP (Contrastive Language-Image Pre-training) uses contrastive learning from noise image-text pairs to excel at recognizing a wide array of c

Reducing the Safety Tax in LLM Safety Alignment with On-Policy Self-Distillation

arXiv:2605.15239v1 Announce Type: new Abstract: Safety alignment often improves robustness to harmful queries at the cost of reasoning ability, a tradeoff known as the safety tax. A common cause is di

Registers Matter for Pixel-Space Diffusion Transformers

arXiv:2605.16147v1 Announce Type: new Abstract: Vision Transformers (ViTs) are known to exhibit high-norm patch-token outliers that degrade feature map quality, a problem effectively mitigated by exti

Reinforcement learning for adaptive interior point methods in convex quadratic programming

arXiv:2509.07404v2 Announce Type: replace-cross Abstract: Quadratic programming is a workhorse of modern nonlinear optimization, control, and data science. Although regularized methods offer convergen

Representation Without Reward: A JEPA Audit for LLM Fine-Tuning

arXiv:2605.15394v1 Announce Type: cross Abstract: Joint-embedding predictive architectures (JEPAs) propose that a model should learn more useful abstractions when trained to predict latent representat

Retrieval-Augmented Large Language Models for Schema-Constrained Clinical Information Extraction

arXiv:2605.15467v1 Announce Type: cross Abstract: Conversational nurse-patient transcripts contain actionable observations, but converting these transcripts into structured representations at scale re

RoadmapBench: Evaluating Long-Horizon Agentic Software Development Across Version Upgrades

arXiv:2605.15846v1 Announce Type: cross Abstract: Coding agents are increasingly deployed in real software development, where a single version iteration requires months of coordinated work across many

RTL-BenchMT: Dynamic Maintenance of RTL Generation Benchmark Through Agent-Assisted Analysis and Revision

arXiv:2605.15537v1 Announce Type: new Abstract: This paper introduces RTL-BenchMT, an agentic framework for dynamically maintaining RTL generation benchmarks. Large Language Models (LLMs) assisted aut

Rule2DRC: Benchmarking LLM Agents for DRC Script Synthesis with Execution-Guided Test Generation

arXiv:2605.15669v1 Announce Type: new Abstract: Manufacturable chip layouts must satisfy thousands of geometry-based design rules, and design rule checking (DRC) enforces them by running executable DR

Run Claude Managed Agents with Vercel Sandbox

model-releasesvercel-blog

This article describes how to run Claude's managed agents within Vercel's Sandbox environment, enabling developers to execute AI agent workloads on Vercel's infrastructure. The integration allows user

Runtime-Orchestrated Second-Order Optimization for Scalable LLM Training

arXiv:2605.16184v1 Announce Type: cross Abstract: Second-order methods offer an attractive path toward more sample-efficient LLM training, but their practical use is often blocked by the systems cost

SaaS-Bench: Can Computer-Use Agents Leverage Real-World SaaS to Solve Professional Workflows?

arXiv:2605.15777v1 Announce Type: new Abstract: Computer-Using Agents (CUAs) are rapidly extending large language models (LLMs) beyond text-based reasoning toward action execution in more complex envi

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery

arXiv:2510.22665v3 Announce Type: replace-cross Abstract: Synthetic Aperture Radar (SAR) is a critical imaging modality due to its all-weather operational capability. Although recent advances in self-

SDOF: Taming the Alignment Tax in Multi-Agent Orchestration with State-Constrained Dispatch

arXiv:2605.15204v1 Announce Type: new Abstract: Multi-agent orchestration frameworks such as LangChain, LangGraph, and CrewAI route tasks through graph-based pipelines but do not enforce the stage con

Searching on a Budget: HW-NAS with 10 Latency Probes

arXiv:2504.00663v2 Announce Type: replace Abstract: Existing hardware-aware NAS (HW-NAS) methods typically assume access to precise information circa the target device, either via analytical approxima

SemanticOpt: Towards LLM-Based Semantic Black-Box Optimization

arXiv:2510.25404v3 Announce Type: replace-cross Abstract: Optimizing an experimental system can be extremely challenging when each experiment is expensive, time-consuming, or difficult to perform. Exi

SGR: A Stepwise Reasoning Framework for LLMs with External Subgraph Generation

arXiv:2605.16117v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated strong capabilities across diverse NLP applications, such as translation, text generation, and question a

ShopGym: An Integrated Framework for Realistic Simulation and Scalable Benchmarking of E-Commerce Web Agents

arXiv:2605.16116v1 Announce Type: new Abstract: Developing and evaluating e-commerce web agents requires environments that preserve meaningful task structure while enabling controllable, reproducible,

SkillSmith: Compiling Agent Skills into Boundary-Guided Runtime Interfaces

arXiv:2605.15215v1 Announce Type: new Abstract: Recently, skills have been widely adopted in large language model (LLM)-based agent systems across various domains. In existing frameworks, skills are t

SkyLink: A Large Vision-Language Model Driven Re-ranking Framework for Cross-View UAV geolocalization

arXiv:2603.08063v3 Announce Type: replace Abstract: Cross-view UAV geolocalization is fundamentally a challenging large-scale image retrieval task, aiming to determine the geographic coordinates of Un

Skyra: AI-Generated Video Detection via Grounded Artifact Reasoning

arXiv:2512.15693v2 Announce Type: replace Abstract: The misuse of AI-driven video generation technologies has raised serious social concerns, highlighting the urgent need for reliable AI-generated vid

SMMBench: A Benchmark for Source-Distributed Multimodal Agent Memory

arXiv:2605.15710v1 Announce Type: new Abstract: Existing benchmarks for multimodal memory reasoning largely evaluate systems within pre-assembled contexts, but under-evaluate whether agents can use ev

Social-Mamba: Socially-Aware Trajectory Forecasting with State-Space Models

arXiv:2605.15424v1 Announce Type: new Abstract: Human trajectory forecasting is crucial for safe navigation in crowded environments, requiring models that balance accuracy with computational efficienc

SOLAR: Self-supervised Joint Learning for Symmetric Multimodal Retrieval

arXiv:2605.15868v1 Announce Type: new Abstract: In this work, we address the critical yet underexplored challenge of symmetric multimodal-to-multimodal (MM2MM) retrieval, where queries and contexts ar

Sparse ActionGen: Accelerating Diffusion Policy with Real-time Pruning

arXiv:2601.12894v2 Announce Type: replace-cross Abstract: Diffusion Policy has dominated action generation due to its strong capabilities for modeling multi-modal action distributions, but its multi-s

STAR: A Stage-attributed Triage and Repair framework for RCA Agents in Microservices

arXiv:2605.15581v1 Announce Type: new Abstract: LLM-based root cause analysis (RCA) agents have recently emerged as a promising paradigm for incident diagnosis in microservice AIOps. However, their re

Steve Bannon and 60+ Trump allies sign a Humans First-led letter urging Trump to mandate government testing and approval of powerful AI models before release (Ashley Gold/Axios)

Ashley Gold / Axios: Steve Bannon and 60+ Trump allies sign a Humans First-led letter urging Trump to mandate government testing and approval of powerful AI models before release — A group of more tha

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StippleDiffusion: Capacity-Constrained Stippling using Controlled Diffusion

arXiv:2605.15816v1 Announce Type: cross Abstract: Stipple patterns, point sets whose local density tracks a target image, are traditionally produced by per-density iterative optimizers, which are slow

Structure Abstraction and Generalization in a Hippocampal-Entorhinal Inspired World Model

arXiv:2605.15733v1 Announce Type: cross Abstract: Humans abstract experiences into structured representations to facilitate pattern inference and knowledge transfer. While the hippocampal-entorhinal (

Structure-BiEval: A Self-Supervised, Dual-Track Framework for Decoupling Structure and Content in LLM Evaluation for Web Information Systems

arXiv:2601.19923v2 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) evolve into the core of Web-based autonomous agents and complex Web Information Systems, their ability to fait

STS: Efficient Sparse Attention with Speculative Token Sparsity

arXiv:2605.15508v1 Announce Type: cross Abstract: The quadratic complexity of attention imposes severe memory and computational bottlenecks on Large Language Model (LLM) inference. This challenge is p

SurvivalPFN: Amortizing Survival Prediction via In-Context Bayesian Inference

arXiv:2605.15488v1 Announce Type: new Abstract: Survival analysis provides a powerful statistical framework for modeling time-to-event outcomes in the presence of censoring. However, selecting an appr

SynthRender and IRIS: Open-Source Framework and Dataset for Bidirectional Sim-Real Transfer in Industrial Object Perception

arXiv:2602.21141v2 Announce Type: replace Abstract: Object perception is fundamental for tasks such as robotic material handling and quality inspection. However, modern supervised deep-learning models

T2T-LA: A Topology-to-Topology LLM Agent for Graph Learning with Neither Feature Access nor Task Knowledge

arXiv:2512.08964v4 Announce Type: replace Abstract: Graph learning aims to convert data into graph representations, which are fundamental to many problems in machine learning for CAD, where circuits,

TACO: General Acrobatic Flight Control via Target-and-Command-Oriented Reinforcement Learning

model-releasesarxiv-cs-ro

arXiv:2503.01125v4 Announce Type: replace Abstract: Although acrobatic flight control has been studied extensively, one key limitation of the existing methods is that they are usually restricted to sp