model releases

ELDOR: A Dataset and Benchmark for Illegal Gold Mining in the Amazon Rainforest

arXiv:2605.15397v1 Announce Type: new Abstract: Illegal gold mining in the Amazon rainforest causes deforestation, water contamination, and long-term ecosystem disruption, yet remains difficult to mon

Model Releases

Elon Musk on “Suicidal Empathy”: Gad Saad has a good way to describe it “Suicidal empathy” - where you prey upon people’s empathy so much th…

DGX agent

Elon Musk on “Suicidal Empathy”: Gad Saad has a good way to describe it “Suicidal empathy” - where you prey upon people’s empathy so much that it becomes suicidal to your own country and culture You f

model-releaseselon-musk--x

18 May 2026

End-to-end plaque counting and virus titration from laboratory plate images with deep learning

arXiv:2605.16008v1 Announce Type: new Abstract: Plaque assays remain the gold standard readout of virus infectivity; however, plaque counting from plate images is labor-intensive and prone to inter-op

Ensemble Monitoring for AI Control: Diverse Signals Outweigh More Compute

arXiv:2605.15377v1 Announce Type: new Abstract: As AI systems are increasingly deployed in autonomous agentic settings at scale, it is important to ensure the actions they take are safe and aligned wi

Ensuring Logic in the Fog: Sound POMDP Synthesis with LTL Objectives

arXiv:2605.12581v1 Announce Type: cross Abstract: Synthesising autonomous agents that can navigate uncertain environments while adhering to complex temporal constraints remains a fundamental challenge

Entity-Centric World Models: Interaction-Aware Masking for Causal Video Prediction

arXiv:2605.15466v1 Announce Type: new Abstract: Learning predictive world models from unlabelled video is a foundational challenge in artificial intelligence. While Joint Embedding Predictive Architec

Evaluating Chinese Ambiguity Understanding in Large Language Models

arXiv:2605.15635v1 Announce Type: new Abstract: Linguistic ambiguity is critical to the robustness of Large Language Models (LLMs), yet existing research focuses mostly on English, with limited attent

Fair outputs, Biased Internals: Causal Potency and Asymmetry of Latent Bias in LLMs for High-Stakes Decisions

arXiv:2605.15217v1 Announce Type: new Abstract: Instruction-tuned language models exhibit behavioural fairness in high-stakes decisions while retaining biased associations in their internal representa

Fast-tracking genetic leads to reverse cellular aging

model-releasesgoogle-deepmind

Google DeepMind's Co-Scientist AI tool helps researchers identify genetic changes that push cells away from senescence toward youthful states in tissues like skin, hair, and muscle. The system scans s

Federated Imputation under Heterogeneous Feature Spaces

arXiv:2605.16099v1 Announce Type: cross Abstract: Federated Learning (FL) enables collaborative training across decentralized clients, but most methods assume aligned feature schemas, an assumption th

Federated Learning of Spiking Neural Networks under Heterogeneous Temporal Resolutions

arXiv:2605.15355v1 Announce Type: new Abstract: Spiking neural networks (SNNs) are biologically inspired energy-efficient models that use sparse binary spike-based communication between neurons, makin

Feedback World Model Enables Precise Guidance of Diffusion Policy

arXiv:2605.15705v1 Announce Type: cross Abstract: World models aim to improve robotic decision making by predicting the consequences of actions. However, in practice, their predictions often become un

Few-Shot Large Language Models for Actionable Triage Categorization of Online Patient Inquiries

arXiv:2605.15680v1 Announce Type: new Abstract: Online patient inquiries are often informal, incomplete, and written before professional assessment, yet they must still be routed to an appropriate lev

FFAvatar: Few-Shot, Feed-Forward, and Generalizable Avatar Reconstruction

arXiv:2605.15320v1 Announce Type: cross Abstract: Avatar reconstruction has traditionally relied on per-subject optimization that requires hours of computation or on expensive preprocessing that limit

FINESSE-Bench: A Hierarchical Benchmark Suite for Financial Domain Knowledge and Technical Analysis in Large Language Models

arXiv:2605.15482v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly being applied to financial analysis, reporting, investment decision support, risk management, compliance,

Flash-GRPO: Efficient Alignment for Video Diffusion via One-Step Policy Optimization

arXiv:2605.15980v1 Announce Type: new Abstract: Group Relative Policy Optimization has emerged as essential for aligning video diffusion models with human preferences, but faces a critical computation

FORGE: Self-Evolving Agent Memory With No Weight Updates via Population Broadcast

arXiv:2605.16233v1 Announce Type: new Abstract: Can LLM agents improve decision-making through self-generated memory without gradient updates? We propose FORGE (Failure-Optimized Reflective Graduation

ForMaT: Dataset for Visually-Grounded Multilingual PDF Translation

arXiv:2605.15794v1 Announce Type: new Abstract: We present ForMaT (Format-Preserving Multilingual Translation), a parallel corpus of 3,956 PDFs across 15 language pairs that preserves original layout

FormulaCode: Evaluating Agentic Optimization on Large Codebases

arXiv:2603.16011v2 Announce Type: replace-cross Abstract: Large language model (LLM) coding agents increasingly operate at the repository level, motivating benchmarks that evaluate their ability to op

From Feedback Loops to Policy Updates: Reinforcement Fine-Tuning for LLM-Based Alpha Factor Discovery

arXiv:2605.15412v1 Announce Type: cross Abstract: Modern quantitative trading increasingly relies on systematic models to extract predictive signals from large-scale financial data, where alpha factor

From Layers to Networks: Comparing Neural Representations via Diffusion Geometry

arXiv:2605.15901v1 Announce Type: new Abstract: Diffusion geometry is a manifold learning framework that uses random walks defined by Markov transition matrices to characterize the geometry of a datas

Frontier Large Language Models Rival State-of-the-Art Planners

arXiv:2511.09378v2 Announce Type: replace Abstract: A series of influential studies established that large language models cannot reliably solve even simple planning tasks. We show that the latest gen

FRWKV+: Adaptive Periodic-Position Branch Interaction for Frequency-Space Linear Time Series Forecasting

arXiv:2605.15690v1 Announce Type: new Abstract: Long-term time series forecasting is essential for decision making in energy, finance, transportation, and healthcare systems. Recent lightweight foreca

Fully Open Meditron: An Auditable Pipeline for Clinical LLMs

arXiv:2605.16215v1 Announce Type: new Abstract: Clinical decision support systems (CDSS) require scrutable, auditable pipelines that enable rigorous, reproducible validation. Yet current LLM-based CDS

Genome-Factory: A Library for Tuning, Deploying, and Interpreting Genomic Foundation Models

arXiv:2509.12266v2 Announce Type: replace-cross Abstract: We introduce Genome-Factory, the first integrated Python library for tuning, deploying, and interpreting genomic foundation models. Our core c

GenShield: Unified Detection and Artifact Correction for AI-Generated Images

arXiv:2605.16122v1 Announce Type: cross Abstract: Diffusion-based image synthesis has made AI-generated images (AIGI) increasingly photorealistic, raising urgent concerns about authenticity in applica

GESD: Beyond Outcome-Oriented Fairness

arXiv:2605.15295v1 Announce Type: cross Abstract: Machine learning (ML) algorithms are increasingly deployed in high-stakes decision-making domains such as loan approvals, hiring, and recidivism predi

GiLT: Augmenting Transformer Language Models with Dependency Graphs

arXiv:2605.15562v1 Announce Type: new Abstract: Augmenting Transformers with linguistic structures effectively enhances the syntactic generalization performance of language models. Previous work in th

Golden Layers and Where to Find Them: Improved Knowledge Editing for Large Language Models Via Layer Gradient Analysis

arXiv:2602.20207v3 Announce Type: replace-cross Abstract: Knowledge editing in Large Language Models (LLMs) aims to update the model's prediction for a specific query to a desired target while preserv

GQA-{mu}P: The maximal parameterization update for grouped query attention

arXiv:2605.15290v1 Announce Type: cross Abstract: Hyperparameter transfer across model architectures dramatically reduces the amount of compute necessary for tuning large language models (LLMs). The m

GQLA: Group-Query Latent Attention for Hardware-Adaptive Large Language Model Decoding

arXiv:2605.15250v1 Announce Type: cross Abstract: Multi-head Latent Attention (MLA), the attention used in DeepSeek-V2/V3, jointly compresses keys and values into a low-rank latent and matches the H10

Graph-Regularized Sparse Autoencoders for LLM Safety Steering

arXiv:2512.06655v3 Announce Type: replace-cross Abstract: Sparse autoencoders (SAEs) are increasingly used to extract activation directions for inference-time steering, but their standard sparsity obj

GRLO: Towards Generalizable Reinforcement Learning in Open-Ended Environments from Zero

arXiv:2605.15464v1 Announce Type: cross Abstract: Post-training has become a crucial step for unlocking the capabilities of large language models, with reinforcement learning (RL) emerging as a critic

HAI-Eval: Measuring Human-AI Synergy in Collaborative Coding

arXiv:2512.04111v2 Announce Type: replace-cross Abstract: LLM-powered coding agents are reshaping the development paradigm. However, existing evaluation systems, neither traditional tests for humans n

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations

arXiv:2605.15216v1 Announce Type: cross Abstract: Always-on AI applications, from environmental sensors to biomedical implants, require ultra-low power consumption. Analog circuits offer a path to sub

Harnessing Unimodality in Semiparametric Contextual Pricing via Oracle Price Map Learning

arXiv:2605.15411v1 Announce Type: cross Abstract: We study contextual dynamic pricing in a semiparametric scalar-index valuation model where the latent value is v_t=mu_ast(mathsf c_t)+xi_t, with an un

Hidden in Memory: Sleeper Memory Poisoning in LLM Agents

arXiv:2605.15338v1 Announce Type: cross Abstract: Large language models are increasingly augmented with persistent memory, allowing assistants to store user-specific information across sessions for pe

Hierarchical and Holistic Open-Vocabulary Functional 3D Scene Graphs for Indoor Spaces

arXiv:2605.15753v1 Announce Type: cross Abstract: Functional 3D scene graphs offer a versatile and flexible representation for 3D scene understanding and robotic manipulation, defined by object nodes,

How do you know your document parser is ready for production? 🤔 Existing benchmarks miss what AI agents actually need. That's the gap Parse…

model-releasesjerry-liu--x

How do you know your document parser is ready for production? 🤔 Existing benchmarks miss what AI agents actually need. That's the gap ParseBench, the first doc OCR benchmark for AI agents, fills. We'l

How to Train Your Advisor: Steering Black-Box LLMs with Advisor Models

arXiv:2510.02453v3 Announce Type: replace-cross Abstract: Frontier language models are deployed as black-box services, where model weights cannot be modified and customization is limited to prompting.

Hybrid LLM-based Intelligent Framework for Robot Task Scheduling

arXiv:2605.15486v1 Announce Type: cross Abstract: This study introduces intelligent frameworks that use Large Language Models (LLMs) to improve task scheduling for construction robots. The LLM is fed

I love AI, it’s pure LLMs I hate. Pure LLMs are basically just autocomplete. Recent progress (e.g. Claude Code) doesn’t show otherwise Rat…

model-releasesgary-marcus--x

I love AI, it’s pure LLMs I hate. Pure LLMs *are* basically just autocomplete. Recent progress (e.g. Claude Code) doesn’t show otherwise Rather, lot of the progress in the last two years has come from

Improved Bounds for Reward-Agnostic and Reward-Free Exploration

arXiv:2602.16363v2 Announce Type: replace Abstract: We study reward-free and reward-agnostic exploration in episodic finite-horizon Markov decision processes (MDPs), where an agent explores an unknown

IndicSafe: A Benchmark for Evaluating Multilingual LLM Safety in South Asia

arXiv:2603.17915v2 Announce Type: replace-cross Abstract: As large language models (LLMs) are deployed in multilingual settings, their safety behavior in culturally diverse, low-resource languages rem

Inductive inference of gradient-boosted decision trees on graphs for insurance fraud detection

arXiv:2510.05676v2 Announce Type: replace Abstract: Graph-based methods are becoming increasingly popular in machine learning due to their ability to model complex data and relations. Insurance fraud

Information-Preserving Domain Transfer with Unlabeled Data in Misspecified Simulation-Based Inference

arXiv:2605.05652v2 Announce Type: replace Abstract: Simulation-based inference (SBI) provides amortized Bayesian parameter inference from simulator-generated data without requiring explicit likelihood

Interaction-Aware Influence Functions for Group Attribution

arXiv:2605.15675v1 Announce Type: cross Abstract: Influence functions approximate how removing a training example changes a quantity of interest, called the target function, such as a held-out loss. T

Introducing MELI: the Mandarin-English Language Interview Corpus

arXiv:2603.27043v2 Announce Type: replace Abstract: We introduce the Mandarin-English Language Interview (MELI) Corpus, an open-source resource of 29.8 hours of speech from 51 Mandarin-English bilingu