model releases

Your AI chatbot is only as good as the data behind it. This n8n template from our friends at @apify shows you how to wire up a RAG pipeline …

model-releasespinecone--x

Your AI chatbot is only as good as the data behind it. This n8n template from our friends at @apify shows you how to wire up a RAG pipeline using Apify + Pinecone + Gemini so your chatbot can answer q

5 Jun 2026

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

YouZhi: Towards High-Concurrency Financial LLMs via Adaptive GQA-to-MLA Transition

arXiv:2606.05868v1 Announce Type: new Abstract: Large language models (LLMs) drive significant financial innovations, yet their high-concurrency deployment is severely bottlenecked by KV cache memory

5 Jun 2026

100-LongBench: Are de facto Long-Context Benchmarks Literally Evaluating Long-Context Ability?

arXiv:2505.19293v2 Announce Type: replace-cross Abstract: Long-context capability is considered one of the most important abilities of LLMs, as a truly long context-capable LLM enables users to effort

4/5 Still came in ~$0.30 under Claude Code’s spend at a similar score. So we added a lightweight Test Agent that writes repo tests and filte…

model-releasesai21-labs--x

4/5 Still came in ~$0.30 under Claude Code’s spend at a similar score. So we added a lightweight Test Agent that writes repo tests and filters failing patches, pushing our final result to 60.9% - surp

5/5 Takeaway: pipeline order is a hyperparameter. If you're already paying for parallel rollouts, reuse them - they're relevant context, not…

model-releasesai21-labs--x

5/5 Takeaway: pipeline order is a hyperparameter. If you're already paying for parallel rollouts, reuse them - they're relevant context, not just candidate answers. Full write-up: [https://www.ai21.co

A Cookbook of 3D Vision: Data, Learning Paradigms, and Application

model-releasesarxiv-cs-cv

arXiv:2606.04291v1 Announce Type: new Abstract: 3D vision has rapidly evolved, driven by increasingly diverse data representations, learning paradigms, and modeling strategies. Yet the field remains f

A couple of weeks ago we started rebuilding the 𝚑𝚏 CLI with AI agents in mind. it now detects when an agent is using it and gives clean, t…

model-releasesclem-delangue--x

A couple of weeks ago we started rebuilding the 𝚑𝚏 CLI with AI agents in mind. it now detects when an agent is using it and gives clean, token-efficient output, next-command hints, and more, all desig

A New Angle on Bones: Robust Pose Estimation in X-Ray and Ultrasound

model-releasesarxiv-cs-cv

arXiv:2606.04700v1 Announce Type: new Abstract: Measuring the angle between bone structures is a routine task in medical image analysis and provides a key quantitative parameter for diagnosis and trea

A Study of the Scale Invariant Signal to Distortion Ratio in Speech Separation with Noisy References

arXiv:2508.14623v2 Announce Type: replace-cross Abstract: This paper examines the implications of using the Scale-Invariant Signal-to-Distortion Ratio (SI-SDR) as both evaluation and training objectiv

A Systematic Evaluation of Positional Bias in Multi-Video Summarization with MLLMs

arXiv:2606.04596v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are increasingly used for video understanding, yet their reliability under multi-video inputs remains poorly un

Activation-Based Active Learning for In-Context Learning: Challenges and Insights

arXiv:2606.05134v1 Announce Type: new Abstract: Deep active learning has previously been explored for LLM in-context sample selection, but not with methods that utilise recent advances in understandin

AdaKoop: Efficient Modeling of Nonlinear Dynamics from Nonstationary Data Streams with Koopman Operator Regression

arXiv:2606.04930v1 Announce Type: cross Abstract: Real-time data analysis requires the ability to accurately and adaptively address nonlinear dynamics in a nonstationary data stream while preserving c

Adaptive Minds: Empowering Agents with LoRA-as-Tools

arXiv:2510.15416v2 Announce Type: replace Abstract: We investigate a framework in which LoRA adapters are treated as callable tools that a base language model can dynamically select and invoke. We hyp

Affordance2Action: Task-Conditioned Scene-level Affordance Grounding for Real-Time Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.04172v1 Announce Type: new Abstract: Task-conditioned manipulation requires grounding instructions to task-relevant functional parts rather than object categories. This setting is scene-dep

Agent Planning Benchmark: A Diagnostic Framework for Planning Capabilities in LLM Agents

arXiv:2606.04874v1 Announce Type: new Abstract: Planning is central to LLM agents: before acting, an agent must decompose goals, select tools, reason over constraints, and decide when a task is infeas

AICompanionBench: Benchmarking LLMs-as-Judges for AI Companion Safety

arXiv:2606.04867v1 Announce Type: new Abstract: As AI companion platforms such as Replika and Character.AI rapidly grow, concerns about unsafe human-AI interactions have intensified. This study introd

AIP: A Graph Representation for Learning and Governing Agent Skills

arXiv:2606.04781v1 Announce Type: new Abstract: Agent Skills today consist largely of free-form prose requiring the agent to read, interpret, and re-derive how to act in every session. This imposes tw

AlgoVeri: An Aligned Benchmark for Verified Code Generation on Classical Algorithms

arXiv:2602.09464v2 Announce Type: replace-cross Abstract: Vericoding refers to the generation of formally verified code from rigorous specifications. Recent AI models show promise in vericoding, but a

Aligning Deep Implicit Preferences by Learning to Reason Defensively

arXiv:2510.11194v3 Announce Type: replace Abstract: Personalized alignment is crucial for enabling Large Language Models (LLMs) to engage effectively in user-centric interactions. However, current met

ALINC: Active Learning for Inductive Node Classification via Graph Sampling

arXiv:2606.04647v1 Announce Type: new Abstract: Active learning (AL) for node classification typically focuses on selecting the most informative nodes for annotation within one or a few large graphs (

An Empirical Audit of Input Encoders for Multi-Channel Signal Transformers

arXiv:2606.04752v1 Announce Type: cross Abstract: Transformers consuming multi-channel scalar signals must embed C simultaneous values into one d_{ext{model}}-dimensional vector per time step. We empi

An Empirical Study of Data Scale, Model Complexity, and Input Modalities in Visual Generalization

arXiv:2606.04409v1 Announce Type: cross Abstract: Modern deep neural networks usually have large parameter scales and nonlinear hierarchical structures, and they have achieved strong performance in co

An Open-Source Two-Stage Computer Vision Pipeline for Fine-Grained Vehicle Classification using Vision Transformers

model-releasesarxiv-cs-cv

arXiv:2606.05149v1 Announce Type: new Abstract: Vehicle body type is a significant determinant of cyclist injury severity in overtaking crashes, yet automated tools for classifying vehicles into injur

Analysis-Driven Procedural Generation of an Engine Sound Dataset with Embedded Control Annotations

arXiv:2603.07584v2 Announce Type: replace-cross Abstract: Computational engine sound modeling is central to the automotive audio industry, particularly for active sound design applications and virtual

And another open-weight release. Nemotron 3 Ultra has an ultra impressive capability:efficiency ratio! Design-wise, it carries forward the M…

model-releasessebastian-raschka--x

And another open-weight release. Nemotron 3 Ultra has an ultra impressive capability:efficiency ratio! Design-wise, it carries forward the Mamba-2-attention hybrid stack and LatentMoE introduced in th

Andon Labs' Real-World AI Evals: Claude calls the FBI, AI CEOs, price cartels, Butter-Bench, & Luna https://latent.space/p/andon @andonlabs …

Andon Labs' Real-World AI Evals: Claude calls the FBI, AI CEOs, price cartels, Butter-Bench, & Luna https://latent.space/p/andon @andonlabs cofounders @lukaspet and @axelbacklund explain why dollar-de

model-releasesswyx--x

ANN Search: Recall What Matters

arXiv:2606.04522v1 Announce Type: cross Abstract: Approximate nearest neighbor (ANN) search has become a core primitive in information retrieval and modern machine learning tasks, from classification

Anthropic details its progress toward recursive self-improvement, and its implications, and says 80%+ of the code merged into its codebase is authored by Claude (Anthropic)

Anthropic: Anthropic details its progress toward recursive self-improvement, and its implications, and says 80%+ of the code merged into its codebase is authored by Claude — Our progress toward recurs

model-releasestechmeme

'As of May 2026, more than 80% of the code we merge into Anthropic’s codebase was authored by Claude.' Matches independent measures. There r…

model-releasesethan-mollick--x

'As of May 2026, more than 80% of the code we merge into Anthropic’s codebase was authored by Claude.' Matches independent measures. There really is no sign this is slowing down (which doesn't mean th

Asana launches AI-powered products to help organizations manage human and agent work

model-releasessiliconangle

Asana Inc. announced today during the company’s Work Innovation Summit in London the launch of a new product suite that helps organizations manage work by humans and artificial intelligence agents usi

AUDDT: A Unified Benchmark Toolkit for Audio and Speech Deepfake Detectors

arXiv:2509.21597v2 Announce Type: replace-cross Abstract: With the prevalence of artificial intelligence (AI)-generated content, such as audio deepfakes, a large body of recent work has focused on dev

AutoLab: Can Frontier Models Solve Long-Horizon Auto Research and Engineering Tasks?

arXiv:2606.05080v1 Announce Type: new Abstract: Scientific and engineering progress is fundamentally a long-horizon iterative process: proposing changes, running experiments, measuring outcomes, and c

Automatic Generation of Titles for Research Papers Using Language Models

arXiv:2606.05085v1 Announce Type: cross Abstract: The title of a research paper conveys its primary idea and, occasionally, its conclusions in a clear and concise manner. Choosing an appropriate title

Bayesian learning for the stochastic shortest path problem

arXiv:2606.04845v1 Announce Type: cross Abstract: Sequential decision-making problems are often modelled as a Markov decision process (MDP). We focus on the stochastic shortest path (SSP) problem, whi

Bayesian Membership Privacy for Graph Neural Networks

arXiv:2606.04069v1 Announce Type: cross Abstract: Existing privacy analyses for Graph Neural Networks (GNNs) largely inherit assumptions from non-graph settings, overlooking structural correlations an

BBOmix: A Tabular Benchmark for Hyperparameter Optimization of Unsupervised Biological Representation Learning

arXiv:2606.05139v1 Announce Type: new Abstract: The rapid advancement of high-throughput sequencing has led to large, high-dimensional omics datasets. Deep unsupervised learning architectures, particu

Benchmarking Living-Screen-Native GUI Agents on Short-Video Platforms

arXiv:2606.04701v1 Announce Type: cross Abstract: GUI agents today assume a static screen, where the world is frozen between two actions. However, real interfaces such as short-video applications viol

Beyond Objective Equivalence: Constraint Injection for LLM-Based Optimization Modeling on Vehicle Routing Problems

arXiv:2606.04816v1 Announce Type: new Abstract: Large language models (LLMs) increasingly translate natural-language optimization problems into executable solver code. Yet for constraint-dense operati

Beyond Retrieval: Learning Compact User Representations for Scalable LLM Personalization

arXiv:2606.04547v1 Announce Type: cross Abstract: Personalizing large language models requires adapting model behavior to individual users while preserving robustness and deployment-scale efficiency.

Beyond Structural Symmetries: Linear Mode Connectivity via Neuron Identifiability

arXiv:2606.04754v1 Announce Type: new Abstract: Many striking phenomena in deep learning, such as linear mode connectivity and the structured behavior of training dynamics, are closely tied to paramet

Bilevel Autoresearch: Meta-Autoresearching Itself

arXiv:2603.23420v2 Announce Type: replace Abstract: If autoresearch is itself a form of research, then autoresearch can be applied to research itself. We present Bilevel Autoresearch, a bilevel framew

BioBlue: Systematic runaway-optimiser-like LLM failure modes on biologically and economically aligned AI safety benchmarks for LLMs with simplified observation format

arXiv:2509.02655v3 Announce Type: replace-cross Abstract: Many AI alignment discussions of 'runaway optimisation' focus on RL agents: unbounded utility maximisers that over-optimise a proxy objective

Biodefense in the Intelligence Age

This document likely examines how artificial intelligence and advanced intelligence capabilities can be applied to biodefense strategies, including disease surveillance, threat detection, and pandemic

model-releasesopenai

BPDA-GMM: Bayesian Probabilistic Data Association via Gaussian Mixture Models for Semantic SLAM

model-releasesarxiv-cs-ro

arXiv:2606.04618v1 Announce Type: new Abstract: Probabilistic data association (PDA) improves semantic SLAM in perceptually aliased scenes, but existing methods often assume a fixed landmark set, reco

Breaking Bad Molecules: Are MLLMs Ready for Structure-Level Molecular Detoxification?

arXiv:2506.10912v4 Announce Type: replace Abstract: Toxicity remains a leading cause of early-stage drug development failure. Despite advances in molecular design and property prediction, the task of

BreastGPT: A Multimodal Large Language Model for the Full Spectrum of Breast Cancer Clinical Routine

arXiv:2606.04911v1 Announce Type: cross Abstract: Breast cancer remains a leading cause of cancer-related mortality among women. Its clinical management requires multimodal reasoning across a clinical

Building The Ph(ysical)AI Layer Of Machine Intelligence

arXiv:2606.04106v1 Announce Type: cross Abstract: Foundation models achieve generalization through massive-scale training on diverse data, but have limitations with transfer to truly unseen domains wi

Bypassing Prompt Guards in Production with Controlled-Release Prompting

arXiv:2510.01529v3 Announce Type: replace Abstract: Ball et al. recently established that prompt filtering for AI alignment faces a fundamental barrier: under standard cryptographic assumptions, no fi