model releases

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

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Exploratory Responsiveness and Adaptive Rigidity under AI-Assisted Optimization

DGX agent

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

model-releasesarxiv-cs-ai

10 Jun 2026

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

Grok Build is pretty good at optimizing my code in one shot. Prompt: I want you to optimize it entirely on GPU to speed it up. Measure two m…

model-releaseselon-musk--x

Grok Build is pretty good at optimizing my code in one shot. Prompt: I want you to optimize it entirely on GPU to speed it up. Measure two metrics: the result must compare with the golden image (CPU)

HarmoView: Harmonizing Multi-View Constraints for Identity-Consistent Video Generation

arXiv:2606.10839v1 Announce Type: new Abstract: Current identity-consistent video generation methods struggle to preserve appearance fidelity under large viewpoint changes. While introducing multi-vie

Here are Fable's pelicans for the different thinking effort levels, plus how much each one cost to generate via the Claude API

model-releasessimon-willison--x

Simon Willison demonstrated Fable's pelican illustrations generated at different Claude API thinking effort levels, showcasing how increased computational investment affects output quality and cost. T

HISTORY LESSON: In 1968 the US, USSR, UK, France, and China signed the Nuclear Non-Proliferation Treaty, declaring nuclear weapons too dange…

model-releasesclem-delangue--x

HISTORY LESSON: In 1968 the US, USSR, UK, France, and China signed the Nuclear Non-Proliferation Treaty, declaring nuclear weapons too dangerous for any more countries to build. All five already had t

How can we assess human-agent interactions? Case studies in software agent design

arXiv:2510.09801v3 Announce Type: replace Abstract: While benchmarks measure the accuracy of LLM-powered agents, they mostly assume full automation, failing to represent the collaborative nature of re

Hyperparameter Learning for Latent Factorization of Tensors for Representation Learning to Large-scale Dynamic Weighted Directed Network

arXiv:2606.09880v1 Announce Type: new Abstract: Large-scale dynamic weighted directed networks (DWDNs) are widely used to model time-varying interactions among nodes. Latent factorization of tensors (

I argued, publicly, AGAINST each of these foolish predictions– and got endless shit for it. Moral: on X, you probably shouldn’t trust the “w…

model-releasesgary-marcus--x

I argued, publicly, AGAINST each of these foolish predictions– and got endless shit for it. Moral: on X, you probably shouldn’t trust the “wisdom” of the crowds. Remember all the AI predictions people

I too have felt the latest Claude's to be too smart its bored. Glad others are noticing the same

model-releasesjerry-liu--x

I too have felt the latest Claude's to be too smart its bored. Glad others are noticing the same Claude Fable 5 thinks document parsing is beneath it It is absolutely crushing on all reasoning-intensi

IDP-Bench: Benchmarking ability of LLMs to protect personal information in interdependent privacy contexts

arXiv:2606.09908v1 Announce Type: cross Abstract: Large language models (LLMs) are becoming widely deployed as personal AI assistants with access to sensitive user data, making privacy a major challen

If Claude Fable stops helping you, you'll never know

model-releasessimon-willison

If Claude Fable stops helping you, you'll never know Jonathon Ready highlights one of the more eyebrow-raising details from the 319 page system card for Fable 5 and Mythos 5. Here's a longer excerpt,

Instruction Finetuning DeepSeek-R1-8B Model Using LoRA and NEFTune

arXiv:2606.10392v1 Announce Type: new Abstract: Financial named-entity recognition (NER) is essential for translating unstructured financial reports and news into structured knowledge graphs. However,

IntentKV: Cross-Turn Intent-Aware KV Cache Pruning for Agent Inference

arXiv:2606.09916v1 Announce Type: cross Abstract: Multi-turn LLM agents fan short queries into long trajectories of tool calls, search results, and intermediate reasoning. Both KV memory and KV read b

Interpretable deep convolutional model for nonlinear multivariate time series in complex systems

arXiv:2501.04339v2 Announce Type: replace-cross Abstract: We introduce the Deep Convolutional Interpreter for Time Series (DCIts), a deep-learning architecture for nonlinear multivariate time series t

Interpretable Temporal Facial-Region Motion Analysis for In-the-Wild Parkinson's Disease Video Classification

arXiv:2606.10088v1 Announce Type: new Abstract: Reduced facial expressivity is a common motor manifestation of Parkinson's disease (PD), often described as hypomimia or facial bradykinesia. This paper

IPSM-Bench: A New Intermediate Phase Segmentation Benchmark in Microstructure Images of Zinc-Based Absorbable Biomaterials

arXiv:2606.11001v1 Announce Type: new Abstract: Zinc-based alloys are indispensable emerging absorbable metallic biomaterials, and their macroscopic performance is governed by microstructural characte

iSAGE: A Human-in-the-Loop Framework for Remote Sensing Semantic Segmentation via Sparse Point Supervision

arXiv:2606.10136v1 Announce Type: new Abstract: Semantic segmentation in remote sensing requires costly pixel-level annotations, and nearly every problem demands a new dataset since models rarely tran

Janus: A Benchmark for Goal-Conditioned Information Distortion in LLMs

arXiv:2606.10852v1 Announce Type: cross Abstract: LLM deception is often evaluated through direct markers such as fabricated claims, explicit lies, or strategic concealment. However, many real-world m

JGRA: Jacobian Geometry Robustness Assessment in NISQ Noise-Aware Quantum Neural Networks

arXiv:2606.09964v1 Announce Type: cross Abstract: The NISQ era places stringent constraints on quantum computation, where noise and decoherence fundamentally limit performance. In classical deep learn

KCSAT-ML: Probing Reasoning Models with Nationwide-Cohort Human Difficulty

model-releasesarxiv-cs-cl

arXiv:2606.10403v1 Announce Type: new Abstract: Math reasoning benchmarks have proliferated, yet most lack a per-item difficulty signal grounded in actual human performance. We introduce KCSAT-ML, a d

Kwai Keye-VL-2.0 Technical Report

arXiv:2606.10651v1 Announce Type: new Abstract: We introduce Kwai Keye-VL-2.0-30B-A3B, an open-source Mixture-of-Experts (MoE) multimodal foundation model designed to advance long-video understanding

LakeQA: An Exploratory QA Benchmark over a Million-Scale Data Lake

arXiv:2606.10460v1 Announce Type: cross Abstract: Recent large language models (LLMs) have shown rapid progress in reading-based question answering (QA), where evidence is explicitly provided or can b

Latent Guided Sampling for Combinatorial Optimization

arXiv:2506.03672v2 Announce Type: replace-cross Abstract: Combinatorial Optimization problems are widespread in domains such as logistics, manufacturing, and drug discovery, yet their NP-hard nature m

Less Context, Better Agents: Efficient Context Engineering for Long-Horizon Tool-Using LLM Agents

arXiv:2606.10209v1 Announce Type: new Abstract: Large language models deployed as autonomous agents for enterprise workflows face a key challenge: verbose tool responses from enterprise systems can ca

Less Context, More Accuracy: A Bi-Temporal Memory Engine for LLM Agents Where a Lean Retrieved Context Beats the Full History

arXiv:2606.09900v1 Announce Type: cross Abstract: Long-term memory is the missing layer for LLM agents: across sessions they forget, and the common workaround -- replaying the whole history into the p

Letter: Texas Governor Greg Abbott released regulatory recommendations for state lawmakers to ensure that data centers shoulder the costs of their growth (The Texas Tribune)

The Texas Tribune: Letter: Texas Governor Greg Abbott released regulatory recommendations for state lawmakers to ensure that data centers shoulder the costs of their growth — The recommendations for l

model-releasestechmeme

LIBERO-Occ: Evaluating and Improving Vision-Language-Action Models under Scene-Induced Occlusion via Viewpoint Imagination

arXiv:2606.10862v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models achieve strong performance on standard manipulation benchmarks, but most evaluations assume that task-relevant obj

LLM-as-a-Discriminator: When Synthetic Tables Still Look Real

arXiv:2606.09865v1 Announce Type: new Abstract: Privacy and data sharing are often in tension. Many organizations use synthetic data to reduce privacy risk and still share useful data. For tabular dat

LLM-Based Code Documentation Generation and Multi-Judge Evaluation

arXiv:2606.09852v1 Announce Type: cross Abstract: High-quality source code documentation is vital yet often neglected, especially in critical domains like healthcare where reliability and maintainabil