model releases

Great feature but is this true “multi-player mode”? I’d say no, honestly. I know everyone is psyched for this, and I’m sure my team will get value from it, but what has been more valuable is having ou

arXiv:2603.20510v2 Announce Type: replace Abstract: Language models often lack grounded reasoning capabilities in specialized domains where training data is scarce but bespoke systems excel. We introd

arXiv:2606.24551v1 Announce Type: new Abstract: Computer-use agents can execute software tasks through either graphical interfaces or programmatic command interfaces, but existing evaluations confound

arXiv:2606.23843v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are typically pre-trained on large-scale image-text datasets to capture semantic correspondences between visual content an

Jagmeet Singh / TechCrunch: Hang Ten Systems, led by former Infosys CEO Vishal Sikka, launches with a $32M seed led by Mayfield to help enterprises use AI to run software at a lower cost — For decades

arXiv:2606.24650v1 Announce Type: new Abstract: We present Harmonic, a hierarchical state space model (SSM) for language modeling. The architecture stacks three recurrent levels at progressively slowe

HelloTwin.ai GmbH today announced what it calls an accountable artificial intelligence AI twin that holds business intelligence and goals in a single source of truth. HelloTwin said it built its data

arXiv:2606.23702v1 Announce Type: cross Abstract: Modulation recognition systems rely on heterogeneous signal representations. 2D signal-image modalities such as time-frequency and cyclostationary map

arXiv:2606.24557v1 Announce Type: new Abstract: Heterogeneous Knowledge Distillation (HKD) aims to transfer knowledge across varying architectures (e.g., from Transformer to CNN) but inherently suffer

arXiv:2606.24133v1 Announce Type: cross Abstract: The composition of training data, governed by the diversity of sources and their mixing strategy, is a cornerstone of Large Language Model (LLM) pre-t

arXiv:2606.23238v2 Announce Type: replace Abstract: Logical reasoning is essential for reliable AI, yet existing benchmarks are largely first-order-logic-centric, focusing on object-level deduction ov

arXiv:2606.16821v2 Announce Type: replace Abstract: Large language model (LLM)-based search agents synthesize open-web content into actionable recommendations on behalf of users, creating a risk that

I’m headed to San Francisco for AI Engineer World's Fair next week. Two things. I'm giving a talk Tuesday, June 30: 'The unreasonable effectiveness of BM25 for agentic search.' GPT-5 is shockingly goo

I’m very excited about this article from @OpenAI on my attempt to use GPT-5 Pro to understand the results of an experiment we did several years ago. Remarkably, GPT-5 Pro figured out the key mechanism

Introducing AI IQ Bio: the most comprehensive set of biotech benchmarks in the world ...& Bio IQ: the most comprehensive 'biotech capabilities index' ever produced Benchmark sources include benchmarks

I cannot provide an accurate summary for this entry. The URL and source attribution appear inconsistent (title credits Yohei Nakajima but URL references a different user), and the post references prod

arXiv:2606.23032v2 Announce Type: replace Abstract: Finance Agent v2 (by Vals AI) has emerged as the reference benchmark for evaluating both Anthropic Claude and OpenAI ChatGPT frontier language model

arXiv:2606.24570v1 Announce Type: new Abstract: Vision-language contrastive pretraining has become the dominant recipe for 3D medical foundation models, leveraging the large volumes of paired scans an

Kahlil Watson hit his first Major League Baseball home run, a game-tying shot to right field while playing for the Cleveland Guardians. The post was shared on the Guardians' social media account to hi

arXiv:2606.17927v2 Announce Type: replace-cross Abstract: Kolmogorov-Arnold Networks (KANs) have recently emerged as a promising alternative to traditional multilayer perceptrons by replacing linear w

arXiv:2606.22419v2 Announce Type: replace Abstract: A recent Nature Medicine study reports that general-purpose frontier LLMs outperform specialized retrieval-augmented clinical tools on medical bench

arXiv:2606.24825v1 Announce Type: new Abstract: Part-of-Speech (POS) tagging is a foundational NLP task underpinning machine translation, information extraction, and syntactic parsing. Despite Marathi

arXiv:2606.24669v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong potential for planning and sequential decision-making, but prior work often relies on using them as direc

arXiv:2606.23566v2 Announce Type: replace Abstract: Language-specific tokenizers improve tokenization quality and the downstream performance of models on those languages. However, using such a tokeniz

arXiv:2606.24808v1 Announce Type: cross Abstract: Quantum computers could outperform classical machines on important problems, but only if the errors that pervade quantum hardware can be corrected at

arXiv:2606.23957v1 Announce Type: new Abstract: Learning Koopman operators with autoencoders enables linear prediction in a latent space, but long-horizon rollouts often drift off the learned manifold

arXiv:2606.23993v1 Announce Type: cross Abstract: High-throughput scientific facilities such as the Large Hadron Collider depend on real-time event filtering (extit{triggering}) under tight constraint

arXiv:2606.23716v1 Announce Type: cross Abstract: Legal AI benchmark research frequently invokes the assumption that large language models can improve access to justice, including for people who canno

arXiv:2606.24311v1 Announce Type: new Abstract: As large language model (LLM) agents are applied to longer tasks, they increasingly modify workspace state across multiple rounds of iteration. However,

arXiv:2606.24173v1 Announce Type: cross Abstract: On-device fault detection enables real-time diagnostics without cloud dependency, but deploying machine learning models on resource-constrained hardwa

arXiv:2602.18934v2 Announce Type: replace Abstract: Membership inference attacks (MIAs) threaten the privacy of machine learning models by revealing whether a specific data point was used during train

arXiv:2509.17773v2 Announce Type: replace Abstract: The rapid progress of image-guided video generation (I2V) has raised concerns about its potential misuse in misinformation and fraud, underscoring t

arXiv:2606.23742v1 Announce Type: cross Abstract: Physical neural networks promise low-power machine learning by computing directly with analogue device physics, but most architectures force nonlinear

arXiv:2606.24011v1 Announce Type: cross Abstract: A crucial assumption in graph signal processing (GSP) is the existence of an underlying graph that captures the pairwise similarities between nodes, a

arXiv:2505.10931v4 Announce Type: replace Abstract: Single-source remote sensing object detection using optical or SAR images struggles in complex environments. Optical images offer rich textural deta

arXiv:2606.23766v1 Announce Type: cross Abstract: The detection and atmospheric characterization of exoplanets have entered a new data-intensive era driven by the James Webb Space Telescope and the up

arXiv:2606.23851v1 Announce Type: cross Abstract: This work investigates the implementation of artificial intelligence and machine learning (AI/ML) for real-time monitoring in laser powder bed fusion

arXiv:2506.10520v5 Announce Type: replace-cross Abstract: Graph-based multi-task learning at billion-scale presents a significant challenge, as different tasks correspond to distinct billion-scale gra

arXiv:2407.06136v4 Announce Type: replace Abstract: Few-shot class-incremental learning (FSCIL) aims to incrementally learn novel classes from limited examples while preserving knowledge of previously

arXiv:2606.24479v1 Announce Type: new Abstract: In-camera JPEG previews are ubiquitous in raw image formats and provide an sRGB reference at negligible storage cost. Although existing metadata-based r

arXiv:2606.24155v1 Announce Type: new Abstract: Existing medical AI benchmarks lack process visibility, atomic skill evaluation, and integrated hallucination detection. We introduce MedBench v5, a red

📣📣 Meet Qwen-AgentWorld — a native language world model that simulates 7 agent environments (MCP, Search, Terminal, SWE, Web, OS, Android) within a single model. Environment modeling is the training o

arXiv:2606.24595v1 Announce Type: new Abstract: Long-term memory promises LLM agents that grow more capable across sessions, maintaining an accurate, evolving understanding of the user that interactio

arXiv:2606.24151v1 Announce Type: cross Abstract: Self-evolving agents improve over time by distilling experience from past executions and reusing it in future tasks. Existing systems represent such e

arXiv:2606.23885v1 Announce Type: cross Abstract: Representation alignment has emerged as an effective approach to improve Multimodal Large Language Models (MLLMs) by regularizing their internal repre

arXiv:2606.24078v1 Announce Type: new Abstract: Imitation learning enables robots to acquire complex manipulation skills from demonstrations, but its effectiveness is limited by the cost of collecting