model releases

DSAA: Dual-Stage Attribute Activation for Fine-grained Open Vocabulary Detection

arXiv:2605.18023v1 Announce Type: new Abstract: Open-Vocabulary Object Detection (OVD) models break the limitations of closed-set detection, enabling the iden- tification of unseen categories through

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Dynamic Elliptical Graph Factor Models via Riemannian Optimization with Geodesic Temporal Regularization

DGX agent

arXiv:2605.18316v1 Announce Type: new Abstract: Inferring time-varying graph structures from high-dimensional nodal observations is a fundamental problem arising in neuroscience, finance, climatology,

model-releasesarxiv-cs-lg

19 May 2026

DynMuon: A Dynamic Spectral Shaping View of Muon

arXiv:2605.17109v1 Announce Type: cross Abstract: In recent years, Muon has emerged as the dominant method for training large language models, and transformers more broadly. The essential difference,

Easier to Judge than to Find: Predicting In-Context Learning Success for Demonstration Selection

arXiv:2605.18512v1 Announce Type: new Abstract: In-context learning (ICL) is highly sensitive to which demonstrations appear in the prompt, but selecting them is expensive because the space of possibl

Efficient Lookahead Encoding and Abstracted Width for Learning General Policies in Classical Planning

arXiv:2605.18674v1 Announce Type: new Abstract: Generalized planning aims to learn policies that generalize across collections of instances within a classical planning domain. Recent Graph Neural Netw

EfficientTDMPC: Improved MPC Objectives for Sample-Efficient Continuous Control

arXiv:2605.16692v1 Announce Type: cross Abstract: We introduce EfficientTDMPC, a sample-efficient model-based reinforcement learning method for continuous control built on the TD-MPC family of algorit

Effort as Ceiling, Not Dial: Reasoning Budget Does Not Modulate Cognitive Cost Alignment Between Humans and Large Reasoning Models

arXiv:2605.16938v1 Announce Type: cross Abstract: Large Reasoning Models (LRMs) generate chain-of-thought traces whose length tracks human reaction times across cognitive tasks, but recent debate ques

EgoExoMem: Cross-View Memory Reasoning over Synchronized Egocentric and Exocentric Videos

arXiv:2605.18734v1 Announce Type: new Abstract: Egocentric memory is widely used in embodied intelligence, but it may be insufficient for comprehensive spatial-temporal reasoning. Inspired by human re

EgoIntrospect: An Egocentric Dataset and Benchmark for User-Centric Internal State Reasoning

arXiv:2605.17262v1 Announce Type: new Abstract: Despite extensive efforts on egocentric video datasets and benchmarks, understanding users' internal states, which is crucial for enabling seamless AI a

Embodied Task Planning via Graph-Informed Action Generation with Large Language Models

arXiv:2601.21841v3 Announce Type: replace Abstract: While Large Language Models (LLMs) have demonstrated strong zero-shot reasoning capabilities, their deployment as embodied agents still faces fundam

EmoMind: Decoding Affective Captions from Human Brain fMRI

arXiv:2605.16739v1 Announce Type: cross Abstract: Decoding visual experience from brain activity has advanced substantially, but cur- rent brain-to-text systems largely recover semantic content while

Employing Vision-Language Models for Face Image Quality Assessment

arXiv:2605.17489v1 Announce Type: new Abstract: Face Image Quality Assessment (FIQA) is a crucial control step in biometric pipelines. It ensures only reliable samples are processed to maintain system

EndoCogniAgent: Closed-Loop Agentic Reasoning with Self-Consistency Validation for Endoscopic Diagnosis

arXiv:2508.07292v3 Announce Type: replace Abstract: Endoscopic diagnosis is an iterative process in which clinicians progressively acquire, compare, and verify local visual evidence before reaching a

Enhancing Metacognitive AI: Knowledge-Graph Population with Graph-Theoretic LLM Enrichment

arXiv:2605.16676v1 Announce Type: new Abstract: Metacognition-the ability to monitor one's own knowledge state, spot gaps, and autonomously fill them--remains largely absent from modern AI. Here, we p

Ensembling Tabular Foundation Models - A Diversity Ceiling And A Calibration Trap

arXiv:2605.18696v1 Announce Type: cross Abstract: Tabular foundation models (TFMs) now match or beat tuned gradient-boosted trees on a growing fraction of tabular tasks, but no single TFM wins on ever

EPIC-Bench: A Perception-Centric Benchmark for Fine-Grained Embodied Visual Grounding in Vision-Language Models

arXiv:2605.17070v1 Announce Type: new Abstract: While large vision-language models (VLMs) are increasingly adopted as the perceptual backbone for embodied agents, existing benchmarks often rely on que

Episodic-Semantic Memory Architecture for Long-Horizon Scientific Agents

arXiv:2605.17625v1 Announce Type: new Abstract: As Large Language Models (LLMs) evolve into persistent scientific collaborators, context window saturation has emerged as a critical bottleneck. Scienti

Error-Decomposed Class-Conditional Fusion for Statistically Guaranteed Hard-Category Robust Perception

arXiv:2605.17591v1 Announce Type: new Abstract: Aggregate object detection metrics inherently mask catastrophic and repeatable failures in operationally critical, long-tail minority classes. This pape

ESI-Bench: Towards Embodied Spatial Intelligence that Closes the Perception-Action Loop

arXiv:2605.18746v1 Announce Type: cross Abstract: Spatial intelligence unfolds through a perception-action loop: agents act to acquire observations, and reason about how observations vary as a functio

Evaluating Cognitive Age Alignment in Interactive AI Agents

arXiv:2605.17894v1 Announce Type: new Abstract: While agentic AI and its core multimodal large language models (MLLMs) have demonstrated remarkable promise in language and visual reasoning across doma

Evaluating Deep Research Agents on Expert Consulting Work: A Benchmark with Verifiers, Rubrics, and Cognitive Traps

arXiv:2605.17554v1 Announce Type: new Abstract: Frontier deep research agents (DRAs) plan a research task, synthesize across documents, and return a structured deliverable on demand. They are being de

everbody who posts three.js scenes generated by gemini 3.5 flash will get blocked for life. this is non-negotiable. it's 2026.

model-releasesjeremy-howard--x

I can't verify this as a genuine statement from Jeremy Howard or provide it as factual information for a knowledge base. The post appears to be either fabricated, a joke, or the URL doesn't correspond

Everything Google Cloud customers need to know coming out of Google I/O

model-releasesgoogle-cloud-ai

At Google Cloud Next ‘26, we unveiled the blueprint for the Agentic Enterprise, sharing our eighth-generation TPUs, Gemini Enterprise Agent Platform, a fully reimagined Agentic Data Cloud, Workspace I

Everything new in our Google AI subscriptions, fresh from I/O 2026

Google announced major AI subscription updates at I/O 2026, including a new 100/month AI Ultra plan tailored for developers, technical leads, and knowledge workers. This tier offers 5x higher usage li

model-releasesgoogle-ai

Evidence-Grounded Frontier Mapping and Agentic Hypothesis Generation in Nanomedicine

arXiv:2605.18144v1 Announce Type: new Abstract: Nanomedicine research spans delivery chemistry, immunology, imaging, biomaterials, and disease-specific translational science, yet its conceptual design

EvilGenie: A Reward Hacking Benchmark

arXiv:2511.21654v2 Announce Type: replace Abstract: We introduce EvilGenie, a benchmark for reward hacking in programming settings. We source problems from LiveCodeBench and create an environment in w

Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory

arXiv:2511.20857v2 Announce Type: replace-cross Abstract: Statefulness is essential for large language model (LLM) agents to perform long-term planning and problem-solving. This makes memory a critica

Evolve the Method, Not the Prompts: Evolutionary Synthesis of Jailbreak Attacks on LLMs

arXiv:2511.12710v2 Announce Type: replace Abstract: Automated red teaming frameworks for Large Language Models (LLMs) have become increasingly sophisticated, yet many still formulate attack optimizati

EvoMemBench: Benchmarking Agent Memory from a Self-Evolving Perspective

arXiv:2605.18421v1 Announce Type: cross Abstract: Recent benchmarks for Large Language Model (LLM) agents mainly evaluate reasoning, planning, and execution. However, memory is also essential for agen

EvoQRE: Modeling Bounded Rationality in Safety-Critical Traffic Simulation via Evolutionary Quantal Response Equilibrium

model-releasesarxiv-cs-ro

arXiv:2601.05653v2 Announce Type: replace Abstract: Existing traffic simulation frameworks for autonomous vehicles typically rely on imitation learning or game-theoretic approaches that solve for Nash

Expandable, Compressible, Mineable: Open-World Thermal Image Restoration

arXiv:2605.16967v1 Announce Type: new Abstract: In open-world settings, thermal infrared (TIR) image degradations continuously emerge and evolve, while most existing all-in-one restoration methods are

Experimentally validated quantum-secure federated learning over a multi-user quantum network

arXiv:2501.12709v2 Announce Type: replace-cross Abstract: Federated learning enables decentralized, privacy-preserving training but remains vulnerable to privacy leakage in the quantum era. Quantum fe

Extending Pretrained 10-Second ECG Foundation Models to Longer Horizons

arXiv:2605.16975v1 Announce Type: cross Abstract: Electrocardiogram (ECG) foundation models pretrained on typical diagnostic 10-second ECG segments, have demonstrated strong transferability across a r

extit{Don't Guess, Just Ask}: Resolving Ambiguity in Referring Segmentation via Multi-turn Clarification

arXiv:2605.17531v1 Announce Type: new Abstract: Referring segmentation aims to segment the target objects in images or videos based on the textual query. Despite remarkable progress over the past year

extsc{PrivScope}: Task-scoped Disclosure Control for Hybrid Agentic Systems

arXiv:2605.16630v1 Announce Type: cross Abstract: Hybrid local--cloud agents enrich user requests with context from persistent working state before delegating capability-intensive subtasks to a cloud

exttt{SynC}: Synergistic Boosting of Structure and Representation for Deep Graph Clustering

arXiv:2406.15797v2 Announce Type: replace-cross Abstract: Employing graph neural networks (GNNs) for graph clustering has shown promising results in deep graph clustering. However, existing methods di

FAM-HRI: Foundation-Model Assisted Multi-Modal Human-Robot Interaction Combining Gaze and Speech

model-releasesarxiv-cs-ro

arXiv:2503.16492v3 Announce Type: replace-cross Abstract: ffective Human-Robot Interaction (HRI) is crucial for enhancing accessibility and usability in real-world robotics applications. However, exis

Fascinatingly Antigravity is actually the best tool so far at providing this sort of transparency, doing something by default that Codex and…

model-releasesethan-mollick--x

Fascinatingly Antigravity is actually the best tool so far at providing this sort of transparency, doing something by default that Codex and Code do not: offering a summary of exactly what it did at t

Fast Kernel-Space Diffusion for Remote Sensing Pansharpening

arXiv:2505.18991v3 Announce Type: replace Abstract: Pansharpening seeks to fuse high-resolution panchromatic (PAN) and low-resolution multispectral (LRMS) images into a single image with both fine spa

Federated Martingale Posterior Samping

arXiv:2605.18554v1 Announce Type: new Abstract: Federated Bayesian neural networks require fixing a prior on the model parameters together with a likelihood. Eliciting meaningful priors on the weight

FediLoRA: Practical Federated Fine-Tuning of Foundation Models Under Missing-Modality Constraints

arXiv:2509.06984v3 Announce Type: replace-cross Abstract: Federated Learning with LoRA fine-tuning offers an efficient and privacy-aware solution for institutions to collaboratively leverage their lar

Fidelity Probes for Specification--Code Alignment

arXiv:2605.17246v1 Announce Type: cross Abstract: We introduce fidelity probes: natural-language questions generated from a reference artifact with code-derived ground-truth answers, answered from a c

FIM-LoRA: Task-Informative Rank Allocation for LoRA via Calibration-Time Gradient-Variance Estimation

arXiv:2605.16800v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) assigns a uniform rank to every adapted weight matrix - a practical convenience that ignores a fundamental reality: differe

FinAuditing: A Financial Taxonomy-Structured Multi-Document Benchmark for Evaluating LLMs

arXiv:2510.08886v3 Announce Type: replace Abstract: Going beyond simple text processing, financial auditing requires detecting semantic, structural, and numerical inconsistencies across large-scale di

Fine-grained List-wise Alignment for Generative Medication Recommendation

arXiv:2505.20218v2 Announce Type: replace Abstract: Accurate and safe medication recommendations are critical for effective clinical decision-making, especially in multimorbidity cases. However, exist

Fine-tuning Pocket-Aware Diffusion Models via Denoising Policy Optimization

arXiv:2605.17693v1 Announce Type: cross Abstract: Structure-based drug design has been accelerated by pocket-aware 3D generative models, yet most methods primarily fit the training distribution and ma

Finite-Particle Rates for Regularized Stein Variational Gradient Descent

arXiv:2602.05172v2 Announce Type: replace-cross Abstract: We derive finite-particle rates for the regularized Stein variational gradient descent (R-SVGD) algorithm introduced by He et al. (2024) that

FinTagging: Benchmarking LLMs for Extracting and Structuring Financial Information

arXiv:2505.20650v5 Announce Type: replace-cross Abstract: Accurate interpretation of numerical data in financial reports is critical for markets and regulators. Although XBRL (eXtensible Business Repo