Search: “model-releases”

Data-Driven Dynamic Assortment in Online Platforms: Learning about Two Sides

arXiv:2606.11118v1 Announce Type: new Abstract: We study a dynamic assortment problem on a two-sided service platform with incomplete information and heterogeneous customers in a discrete-time setting

Model Releases

Data-Driven Runway and Taxiway Exits Prediction of Landing Aircraft: A Case Study at Hartsfield-Jackson Atlanta International Airport

DGX agent

arXiv:2606.11017v1 Announce Type: new Abstract: Airport surface operations increasingly constrain performance at high-throughput hubs. This study examines arrival taxi-in decisions at Hartsfield-Jacks

model-releasesarxiv-cs-lg

10 Jun 2026

datasette-agent 0.2a0

model-releasessimon-willison

Release: datasette-agent 0.2a0 Highlights from the release notes: Tools can now ask the user questions mid-execution. Tools that declare a context parameter receive a ToolContext object, and await con

Day 0 Anthropic Fable 5 in ParseBench: We tested the model's advancements when it comes to document understanding. The model clearly peaks w…

model-releasesjerry-liu--x

Day 0 Anthropic Fable 5 in ParseBench: We tested the model's advancements when it comes to document understanding. The model clearly peaks when it comes to adherence to the original text: 📃 Content fa

DB-3DME: From Dataset to Benchmark for Human-aligned Automatic 3D Mesh Evaluation

arXiv:2606.10142v1 Announce Type: new Abstract: Recent advances in 3D generation have led to substantial improvements in realism, controllability, and efficiency, yet the evaluation of 3D assets remai

Deployment-Time Memorization in Foundation-Model Agents

arXiv:2606.10062v1 Announce Type: new Abstract: Foundation-model agents are increasingly long-lived systems that remember users across interactions, making memorization an explicit deployment-time fun

Detecting Knowledge Gaps from Conversational AI Interactions Using Curriculum Prerequisite Graphs

arXiv:2606.10736v1 Announce Type: cross Abstract: Large online courses generate thousands of student questions directed at conversational AI teaching assistants, yet these interaction logs remain larg

DiffusionGemma

model-releasessimon-willison

DiffusionGemma Last May Google briefly released an experimental Gemini Diffusion model. I tried the preview at the time and recorded it running at 857 tokens/second. It was an exciting model, but Goog

DiffusionGemma: 4x faster text generation

model-releasesgoogle-deepmind

DiffusionGemma is an experimental open model from Google DeepMind that uses text diffusion for exceptionally fast generation, moving beyond sequential token-by-token processing to generate entire bloc

Discovering Interpretable Multi-Parameter Control Policies for Evolutionary Algorithms Using Deep Reinforcement Learning

arXiv:2606.10129v1 Announce Type: new Abstract: While deep Reinforcement Learning (deep-RL) has been increasingly applied to parameter control in evolutionary algorithms, rigorous theoretical analysis

Disjoint or Overlapping? Inference Windowing for Reconstruction-Based Time Series Anomaly Detection

arXiv:2606.09874v1 Announce Type: new Abstract: Reconstruction-based methods are widely used for time series anomaly detection, where models are trained to reconstruct subsequences, and anomalies are

Divide-and-Conquer Modeling for the CTF-4-Science Lorenz Benchmark

arXiv:2606.10084v1 Announce Type: cross Abstract: This work presents a divide-and-conquer modeling strategy for the CTF-4-Science Lorenz benchmark, which evaluates chaotic-system prediction across twe

Divide and Cooperate: Role-Decomposed Multi-Agent LLM Training with Cross-Agent Learning Signals

arXiv:2606.10684v1 Announce Type: cross Abstract: Modern language agents which perform multi-step reasoning have shown strong performance in knowledge-intensive question answering. However, existing a

Do Vision-Language Models See or Guess? Measuring and Reducing Textual-Prior Reliance with a Phrasing-Controlled Benchmark

model-releasesarxiv-cs-cl

arXiv:2606.10400v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly deployed where answers must follow from what is in the image, yet they often answer from textual priors,

Do VLMs Reason Like Engineers? A Benchmark and a Stage-wise Evaluation

arXiv:2606.10833v1 Announce Type: new Abstract: Vision-Language Models (VLMs) demonstrate strong performance on general multimodal reasoning benchmarks, yet their ability to perform engineering reason

Domain Adapted Large Language Models for Additive Manufacturing

arXiv:2603.22017v2 Announce Type: replace Abstract: This work presents a collection of multi-modal domain adapted large language models built upon the instruction tuned variants of open weight models

Don't waste SAM

arXiv:2606.10696v1 Announce Type: new Abstract: Meta AI has recently released the Segment Anything Model (SAM), which demonstrates exceptional zero-shot image segmentation performance across various t

Dual-Branch Gated Fusion for Open-Set Audio Deepfake Source Tracing

arXiv:2606.10223v1 Announce Type: cross Abstract: Attributing a synthetic utterance to its originating system remains an open challenge: closed-set models fail to reject unseen synthesizers and produc

Earth-OneVision: Extending Remote Sensing Multimodal Large Language Models to More Sensor Modalities and Tasks

arXiv:2606.10819v1 Announce Type: cross Abstract: RS-MLLMs enable natural-language understanding and spatial reasoning over earth observation imagery. However, existing models support only a narrow ra

EEVEE: Towards Test-time Prompt Learning in the Real World for Self-Improving Agents

arXiv:2606.11182v1 Announce Type: cross Abstract: In this paper, we propose EEVEE, the first multi-dataset test-time prompt learning framework for LLM agents, enabling test-time prompt learning under

Effective Reinforcement Learning for Agentic Search by Recycling Zero-Variance Queries During Training

arXiv:2606.10709v1 Announce Type: cross Abstract: The use of GRPO-style algorithms has become the standard strategy for training LLM search agents under outcome-only rewards. With these algorithms, a

Effective Training Principles of Physical Reservoirs

arXiv:2606.10130v1 Announce Type: cross Abstract: Reservoir computers benefit from the inherent complexity of optical phenomena, which provide rich, often nonlinear dynamics. However, training directl

Efficient RWKV-based Representation Learning for 3D Point Clouds

arXiv:2606.10395v1 Announce Type: new Abstract: The recent receptance weighted key value (RWKV) model combines RNN-style recurrence, offering a linear-complexity alternative to Transformers' quadratic

Efficient-WAM: A 1B-Parameter World-Action Model with Low-Cost Future Imagination

model-releasesarxiv-cs-ro

arXiv:2606.10040v1 Announce Type: new Abstract: World-Action Models (WAMs) have emerged as a promising paradigm for embodied control by coupling future visual prediction with action generation. Howeve

Enabling Progressive Whole-slide Image Analysis with Multi-scale Pyramidal Network

arXiv:2602.01951v2 Announce Type: replace Abstract: Multiple-instance Learning (MIL) is commonly used for computational pathology (CPath), where multi-scale features are essential for capturing both f

Evaluating Research-Level Math Proofs via Strict Step-Level Verification

arXiv:2606.10799v1 Announce Type: new Abstract: Large Language Models (LLMs) struggle to rigorously verify complex mathematical proofs. Standard global evaluation approaches suffer from 'context poiso

Everyone Operating At The Frontier Satya Nadella, Chairman & CEO, Microsoft, interviewed by @saranormous & @eladgil (No Priors) and @swyx (L…

Everyone Operating At The Frontier Satya Nadella, Chairman & CEO, Microsoft, interviewed by @saranormous & @eladgil (No Priors) and @swyx (Latent Space) Crossover special at Microsoft Build 2026. Summ

model-releasesswyx--x

everything your agents do, in a bucket you own. private by default. session traces, task claims, artifacts — claude code, hermes, whatever y…

model-releasesclem-delangue--x

everything your agents do, in a bucket you own. private by default. session traces, task claims, artifacts — claude code, hermes, whatever you run. and make your agents friends via messaging https://h

Expert-Level Crisis Detection in Mental Health Conversations

arXiv:2606.10380v1 Announce Type: cross Abstract: Real-world crisis intervention is inherently conversational, yet existing research largely focuses on static texts.Real-world crisis intervention is i

Exploratory Responsiveness and Adaptive Rigidity under AI-Assisted Optimization

arXiv:2606.10086v1 Announce Type: new Abstract: This paper develops a theory of exploratory adaptation under AI-assisted optimization. The central argument is that the long-run adaptive effects of AI

Fact-Augmented Lookahead Planning for LLM Agents

arXiv:2506.09171v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly capable, but LLM agents still struggle to plan effectively in interactive, partially observable,

FADA: Accessible fetal ultrasound interpretation and annotation with a selectively distilled unified vision-language model

arXiv:2606.11106v1 Announce Type: cross Abstract: A global shortage of trained sonographers limits prenatal ultrasound screening in low- and middle-income countries, where over half of pregnant women

Failure Modes of Deep Multi-Agent RL in Asynchronous Pricing: Reproducible Triggers, Trace Diagnostics, and a Partial Fix

arXiv:2606.09884v1 Announce Type: cross Abstract: We study two reproducible failure modes of deep multi-agent reinforcement learning in continuous-time pricing markets: (i) tacit cartel formation betw

FailureScope: Cross-Regime Behavioral Diagnosis of Language Model Weaknesses

arXiv:2606.09878v1 Announce Type: new Abstract: Standard benchmarks report aggregate accuracy, but practitioners need to know which specific capabilities a model lacks. We introduce FailureScope, a be

Fisher-Guided Progressive Parameter Selection for Adaptive Fine-Tuning

arXiv:2606.10196v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning (PEFT) aims to adapt pretrained models with a small trainable parameter subset, however, most existing methods choose

Flaws in the LLM Automation Narrative

arXiv:2606.11166v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly described as performing at the level of human experts on knowledge economy tasks. These claims are prima

FreshRetailNet-LT: A Stockout-Annotated Censored Demand Dataset for Latent Demand Recovery and Forecasting in Fresh Retail

arXiv:2505.16319v3 Announce Type: replace Abstract: Accurate demand estimation is critical for the retail business in guiding the inventory and pricing policies of perishable products. However, it fac

From data to decisions: how LSEG is scaling trusted AI

LSEG (London Stock Exchange Group) is implementing trusted AI systems to enhance decision-making processes across its financial services operations. The article likely discusses how LSEG is leveraging

model-releasesopenai

From Observation to Intervention: A Causal Audit of Expert Importance in Mixture-of-Experts Models

model-releasesarxiv-cs-cl

arXiv:2606.10703v1 Announce Type: cross Abstract: Interpretability methods routinely use population-level summary statistics over observed model behaviour to license claims about the effects of target

From Patches to Patients: A study of the tile-to-slide performance transferability in Digital Pathology

arXiv:2606.10778v1 Announce Type: new Abstract: Foundation Models (FMs) have recently redefined the state-of-the-art in histopathology by providing robust representations for whole-slide image (WSI) a

Frontier Coding Agents Use Metaprogramming to Adapt to Unfamiliar Programming Languages

arXiv:2606.10933v1 Announce Type: new Abstract: LLM-based coding agents are usually evaluated in familiar software settings: mainstream languages, common libraries, and public repositories. These benc

Gaming AI-Assisted Peer Reviews Poses New Risks to the Scientific Community

arXiv:2606.10159v1 Announce Type: cross Abstract: AI is increasingly used to support scientific peer review, from manuscript screening, reviewer assistance to editorial triage. Although such systems p

Geometry-Aware Reinforcement Learning for 2D Irregular Nesting

arXiv:2606.10611v1 Announce Type: cross Abstract: Traditional heuristic solvers for the 2D irregular nesting problem share a fundamental limitation: they are blind to polygon geometry, relying on guid

GhazalBench: Evaluating LLM Understanding and Canonical Surface-Form Access in Persian Ghazals

model-releasesarxiv-cs-cl

arXiv:2603.09979v2 Announce Type: replace Abstract: Persian poetry plays an active role in Iranian cultural practice, where verses by canonical poets such as Hafez are frequently quoted, paraphrased,

GitInject: Real-World Prompt Injection Attacks in AI-Powered CI/CD Pipelines

arXiv:2606.09935v1 Announce Type: cross Abstract: AI-powered agents are increasingly embedded in continuous integration and continuous delivery/deployment (CI/CD) pipelines to autonomously review pull

Google introduces DiffusionGemma, an experimental 26B-parameter open model that uses text diffusion for faster text generation compared to autoregressive models (The Keyword)

The Keyword: Google introduces DiffusionGemma, an experimental 26B-parameter open model that uses text diffusion for faster text generation compared to autoregressive models — Our newest open experime

model-releasestechmeme

Google’s Gemini 3.5 Live Translate enables realistic translation at the speed of natural conversations

model-releasessiliconangle

Google LLC’s newest artificial intelligence tool promises to bring real-time translation to every smartphone user, enabling more natural and fluid conversations between speakers of different languages

GRID: Scaling Task-Agnostic Inference in Continual Prompt Tuning

arXiv:2507.14725v4 Announce Type: replace-cross Abstract: Prompt-based continual learning (CL) offers a parameter-efficient way to adapt large language models (LLMs) across task sequences. However, ex