model releases

continuing my HTML era, I had so much fun talking with Claire at Code w/ Claude about staying in the loop with long running agents

continuing my HTML era, I had so much fun talking with Claire at Code w/ Claude about staying in the loop with long running agents Soooo @trq212 has straight up changed my life with these 5 words: 'HT

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Model Releases

COPRA: Conditional Parameter Adaptation with Reinforcement Learning for Video Anomaly Detection

DGX agent

arXiv:2605.15325v1 Announce Type: new Abstract: Vision-language models (VLMs) have shown strong performance in video anomaly detection (VAD) while providing interpretable predictions. However, existin

model-releasesarxiv-cs-cv

18 May 2026

CryptoBench: A Dynamic Benchmark for Expert-Level Evaluation of LLM Agents in Cryptocurrency

arXiv:2512.00417v5 Announce Type: replace Abstract: This paper introduces CryptoBench, the first expert-curated, dynamic benchmark designed to rigorously evaluate the real-world capabilities of Large

Decentralized LoRA augmented transformer with multi-scale feature learning for secured eye diagnosis

arXiv:2505.06982v3 Announce Type: replace Abstract: Accurate and privacy-preserving diagnosis of ophthalmic diseases remains a critical challenge in medical imaging, particularly given the limitations

Decouple Searching from Training: Scaling Data Mixing via Model Merging for Large Language Model Pre-training

arXiv:2602.00747v2 Announce Type: replace-cross Abstract: Determining an effective data mixture is a key factor in Large Language Model (LLM) pre-training, where models must balance general competence

Deep Pre-Alignment for VLMs

arXiv:2605.15300v1 Announce Type: new Abstract: Most Vision Language Models (VLMs) directly map outputs from ViT encoders to the LLM via a lightweight projector. While effective, recent analysis sugge

DeepSlide: From Artifacts to Presentation Delivery

arXiv:2605.15202v1 Announce Type: new Abstract: Presentations are a primary medium for scholarly communication, yet most AI slide generators optimize the artifact (a visually plausible deck) while und

Dell + Nvidia

model-releasesclem-delangue--x

Dell + Nvidia Media 'We give you model choice, without infrastructure chaos' — @MichaelDell, live from #DellTechWorld 🎤 Kimi K2.6, DeepSeek V4 Pro, GLM 5.1, MiniMax M2.7 & DeepSeek V4 Flash are now on

DetectRL-X: Towards Reliable Multilingual and Real-World LLM-Generated Text Detection

arXiv:2605.15518v1 Announce Type: new Abstract: The effective detection and governance of Large Language Model (LLM) generated content has become increasingly critical due to the growing risk of misus

Deterministic Coreset for Lp Subspace

arXiv:2601.00361v3 Announce Type: replace-cross Abstract: We introduce the first iterative algorithm for constructing a arepsilon-coreset that guarantees deterministic ell_p subspace embedding for any

Deterministic Event-Graph Substrates as World Models for Counterfactual Reasoning

arXiv:2605.15967v1 Announce Type: new Abstract: We study event-graph substrates: a class of world models that represent agent state as an append-only log of typed RDF triples and answer counterfactual

DexJoCo: A Benchmark and Toolkit for Task-Oriented Dexterous Manipulation on MuJoCo

model-releasesarxiv-cs-ro

arXiv:2605.16257v1 Announce Type: new Abstract: Achieving human-level manipulation requires dexterous robotic hands capable of complex object interactions. Advancing such capabilities further demands

Diagonal Adaptive Non-local Observables on Quantum Neural Networks

arXiv:2605.15410v1 Announce Type: cross Abstract: Adaptive Non-local Observables (ANOs) have shown that making quantum observables dynamic can substantially enlarge the function space of Variational Q

DimMem: Dimensional Structuring for Efficient Long-Term Agent Memory

arXiv:2605.15759v1 Announce Type: new Abstract: Large language model (LLM) agents require long-term memory to leverage information from past interactions. However, existing memory systems often face a

Dynamic Chunking for Diffusion Language Models

arXiv:2605.15676v1 Announce Type: new Abstract: Block discrete diffusion language models factorize a sequence autoregressively over fixed-size positional blocks, decoupling within-block parallel denoi

Echo-Forcing: A Scene Memory Framework for Interactive Long Video Generation

arXiv:2605.16003v1 Announce Type: new Abstract: Autoregressive video diffusion models enable open-ended generation through local attention and KV caching. However, existing training-free long-video op

EduVQA: Towards Concept-Aware Assessment of Educational AI-Generated Videos

arXiv:2603.03066v2 Announce Type: replace Abstract: Existing AI-generated video quality assessment (AIGVQA) methods mainly focus on global perceptual realism and coarse text-video alignment, while ove

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

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…

model-releaseselon-musk--x

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

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