model releases

Embedding Arithmetic: A Lightweight, Tuning-Free Framework for Post-hoc Bias Mitigation in Text-to-Image Models

arXiv:2604.18167v1 Announce Type: new Abstract: Modern text-to-image (T2I) models amplify harmful societal biases, challenging their ethical deployment. We introduce an inference-time method that reli

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EmbodiedLGR: Integrating Lightweight Graph Representation and Retrieval for Semantic-Spatial Memory in Robotic Agents

DGX agent

arXiv:2604.18271v1 Announce Type: new Abstract: As the world of agentic artificial intelligence applied to robotics evolves, the need for agents capable of building and retrieving memories and observa

model-releasesarxiv-cs-ro

21 Apr 2026

Emergent Misalignment via In-Context Learning: Narrow in-context examples can produce broadly misaligned LLMs

arXiv:2510.11288v4 Announce Type: replace Abstract: Recent work has shown that narrow finetuning can produce broadly misaligned LLMs, a phenomenon termed emergent misalignment (EM). While concerning,

Employing General-Purpose and Biomedical Large Language Models with Advanced Prompt Engineering for Pharmacoepidemiologic Study Design

arXiv:2604.17988v1 Announce Type: new Abstract: Background: The potential of large language models (LLMs) to automate and support pharmacoepidemiologic study design is an emerging area of interest, ye

End-to-end Listen, Look, Speak and Act

arXiv:2510.16756v2 Announce Type: replace-cross Abstract: Human interaction is inherently multimodal and full-duplex: we listen while watching, speak while acting, and fluidly adapt to turn-taking and

Enhancing Continual Learning of Vision-Language Models via Dynamic Prefix Weighting

arXiv:2604.18075v1 Announce Type: new Abstract: We investigate recently introduced domain-class incremental learning scenarios for vision-language models (VLMs). Recent works address this challenge us

Enhancing Glass Surface Reconstruction via Depth Prior for Robot Navigation

arXiv:2604.18336v1 Announce Type: cross Abstract: Indoor robot navigation is often compromised by glass surfaces, which severely corrupt depth sensor measurements. While foundation models like Depth A

ENTIRE: Learning-based Volume Rendering Time Prediction

arXiv:2501.12119v3 Announce Type: replace-cross Abstract: We introduce ENTIRE, a novel deep learning-based approach for fast and accurate volume rendering time prediction. Predicting rendering time is

Error as Signal: Stiffness-Aware Diffusion Sampling via Embedded Runge-Kutta Guidance

arXiv:2603.03692v2 Announce Type: replace Abstract: Classifier-Free Guidance (CFG) has established the foundation for guidance mechanisms in diffusion models, showing that well-designed guidance proxi

ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection

arXiv:2410.04509v3 Announce Type: replace Abstract: As the field of Multimodal Large Language Models (MLLMs) continues to evolve, their potential to revolutionize artificial intelligence is particular

ESsEN: Training Compact Discriminative Vision-Language Transformers in a Low-Resource Setting

arXiv:2604.18452v1 Announce Type: cross Abstract: Vision-language modeling is rapidly increasing in popularity with an ever expanding list of available models. In most cases, these vision-language mod

Evaluating Multimodal LLMs for Inpatient Diagnosis: Real-World Performance, Safety, and Cost Across Ten Frontier Models

arXiv:2604.16980v1 Announce Type: new Abstract: Background: Large language models (LLMs) are increasingly proposed for diagnostic support, but few evaluations use real-world multimodal inpatient data,

Evaluating Tool-Using Language Agents: Judge Reliability, Propagation Cascades, and Runtime Mitigation in AgentProp-Bench

arXiv:2604.16706v1 Announce Type: cross Abstract: Automated evaluation of tool-using large language model (LLM) agents is widely assumed to be reliable, but this assumption has rarely been validated a

EvoCoT: Overcoming the Exploration Bottleneck in Reinforcement Learning

arXiv:2508.07809v5 Announce Type: replace Abstract: Reinforcement learning with verifiable reward (RLVR) has become a promising paradigm for post-training large language models (LLMs) to improve their

Exploring Boundary-Aware Spatial-Frequency Fusion for Camouflaged Object Detection

arXiv:2604.17879v1 Announce Type: new Abstract: Camouflaged Object Detection is challenging due to the high degree of similarity between camouflaged objects and their surrounding backgrounds. Current

FaithLens: Detecting and Explaining Faithfulness Hallucination

arXiv:2512.20182v3 Announce Type: replace Abstract: Recognizing whether outputs from large language models (LLMs) contain faithfulness hallucination is crucial for real-world applications, e.g., retri

Falcon flies every few days. You can see launches in person from Florida or California.

model-releaseselon-musk--x

SpaceX's Falcon rockets conduct frequent launches occurring every few days, with public viewing opportunities available at launch facilities in Florida and California. This statement reflects SpaceX's

FedLLM: A Privacy-Preserving Federated Large Language Model for Explainable Traffic Flow Prediction

arXiv:2604.16612v1 Announce Type: new Abstract: Traffic prediction plays a central role in intelligent transportation systems (ITS) by supporting real-time decision-making, congestion management, and

FedOBP: Federated Optimal Brain Personalization through Cloud-Edge Element-wise Decoupling

arXiv:2604.16574v1 Announce Type: new Abstract: Federated Learning (FL) faces challenges from client data heterogeneity and resource-constrained mobile devices, which can degrade model accuracy. Perso

Finding Culture-Sensitive Neurons in Vision-Language Models

arXiv:2510.24942v2 Announce Type: replace-cross Abstract: Despite their impressive performance, vision-language models (VLMs) still struggle on culturally situated inputs. To understand how VLMs proce

FireScope: Wildfire Risk Prediction with a Chain-of-Thought Oracle

arXiv:2511.17171v4 Announce Type: replace Abstract: Predicting wildfire risk is a reasoning-intensive spatial problem that requires the integration of visual, climatic, and geographic factors to infer

FLARE: A Data-Efficient Surrogate for Predicting Displacement Fields in Directed Energy Deposition

arXiv:2604.16649v1 Announce Type: new Abstract: Directed energy deposition (DED) produces complex thermo-mechanical responses that can lead to distortion and reduced dimensional accuracy of a manufact

FLARE: Task-agnostic embedding model evaluation through a normalization process

arXiv:2604.17344v1 Announce Type: cross Abstract: When task-specific labels are not available, it becomes difficult to select an embedding model for a specific target corpus. Existing labelless measur

FlashFPS: Efficient Farthest Point Sampling for Large-Scale Point Clouds via Pruning and Caching

arXiv:2604.17720v1 Announce Type: cross Abstract: Point-based Neural Networks (PNNs) have become a key approach for point cloud processing. However, a core operation in these models, Farthest Point Sa

Flexible Aspect Ratios ChatGPT Images 2.0 supports aspect ratios as wide as 3:1 and as tall as 1:3. It can generate outputs that are ready t…

Flexible Aspect Ratios ChatGPT Images 2.0 supports aspect ratios as wide as 3:1 and as tall as 1:3. It can generate outputs that are ready to fit the formats you need, from wide banners and presentati

model-releasesopenai--x

FLiP: Towards understanding and interpreting multimodal multilingual sentence embeddings

arXiv:2604.18109v1 Announce Type: new Abstract: This paper presents factorized linear projection (FLiP) models for understanding pretrained sentence embedding spaces. We train FLiP models to recover t

Flow marching for a generative PDE foundation model

arXiv:2509.18611v2 Announce Type: replace Abstract: Pretraining on large-scale collections of PDE-governed spatiotemporal trajectories has recently shown promise for building generalizable models of d

For clarity, we're running a small test on ~2% of new prosumer signups. Existing Pro and Max subscribers aren't affected.

model-releasesboris-cherny--x

For clarity, we're running a small test on ~2% of new prosumer signups. Existing Pro and Max subscribers aren't affected. Anthropic just pulled Claude Code from the Pro plan. Pro users wanting it need

Forecast Sports Outcomes under Efficient Market Hypothesis: Theoretical and Experimental Analysis of Odds-Only and Generalised Linear Models

arXiv:2604.17194v1 Announce Type: cross Abstract: Converting betting odds into accurate outcome probabilities is a fundamental challenge in order to use betting odds as a benchmark for sports forecast

Forecasting Ionospheric Irregularities on GNSS Lines of Sight Using Dynamic Graphs with Ephemeris Conditioning

arXiv:2604.18379v1 Announce Type: new Abstract: Most data-driven ionospheric forecasting models operate on gridded products, which do not preserve the time-varying sampling structure of satellite-base

FOREVER: Forgetting Curve-Inspired Memory Replay for Language Model Continual Learning

arXiv:2601.03938v2 Announce Type: replace-cross Abstract: Continual learning (CL) for large language models (LLMs) aims to enable sequential knowledge acquisition without catastrophic forgetting. Memo

Frankentext: Stitching random text fragments into long-form narratives

arXiv:2505.18128v4 Announce Type: replace Abstract: We introduce Frankentexts, a long-form narrative generation paradigm that treats an LLM as a composer of existing texts rather than as an author. Gi

FregeLogic at SemEval 2026 Task 11: A Hybrid Neuro-Symbolic Architecture for Content-Robust Syllogistic Validity Prediction

arXiv:2604.18328v1 Announce Type: new Abstract: We present FregeLogic, a hybrid neuro-symbolic system for SemEval-2026 Task 11 (Subtask 1), which addresses syllogistic validity prediction while reduci

Freshness-Aware Prioritized Experience Replay for LLM/VLM Reinforcement Learning

arXiv:2604.16918v1 Announce Type: new Abstract: Reinforcement Learning (RL) has achieved impressive success in post-training Large Language Models (LLMs) and Vision-Language Models (VLMs), with on-pol

Friendly Machines is happening next Tuesday! We’re exploring how Hermes by @NousResearch and Claude are used to build useful agents: – live …

model-releasesnous-research--x

Friendly Machines is happening next Tuesday! We’re exploring how Hermes by @NousResearch and Claude are used to build useful agents: – live demos – Q&A with @NousResearch team – discuss your workflows

FRIGID: Scaling Diffusion-Based Molecular Generation from Mass Spectra at Training and Inference Time

arXiv:2604.16648v1 Announce Type: new Abstract: In this work, we present FRIGID, a framework with a novel diffusion language model that generates molecular structures conditioned on mass spectra via i

From developer desks to the whole organization: Running Claude Cowork in Amazon Bedrock

model-releasesaws-ml-blog

Today, we're excited to announce Claude Cowork in Amazon Bedrock. You can now run Cowork and Claude Code Desktop through Amazon Bedrock, directly or using an LLM gateway. In this post, we walk through

From Handwriting to Structured Data: Benchmarking AI Digitisation of Handwritten Forms

arXiv:2604.16504v1 Announce Type: new Abstract: Manual digitisation of structured handwritten documents is slow and costly. We benchmark 17 leading frontier multi-modal large language models and open-

From Heads to Neurons: Causal Attribution and Steering in Multi-Task Vision-Language Models

arXiv:2604.17941v1 Announce Type: cross Abstract: Recent work has increasingly explored neuron-level interpretation in vision-language models (VLMs) to identify neurons critical to final predictions.

From Inheritance to Saturation: Disentangling the Evolution of Visual Redundancy for Architecture-Aware MLLM Inference Acceleration

arXiv:2604.16462v1 Announce Type: new Abstract: High-resolution Multimodal Large Language Models (MLLMs) face prohibitive computational costs during inference due to the explosion of visual tokens. Ex

From keynote to the terminal: Join our Next ‘26 developer livestreams

model-releasesgoogle-cloud-ai

The main stage at Google Cloud Next is where the vision is set. This year, we’re bridging the gap between those massive 'Cloud-scale' announcements and your local terminal. We are thrilled to announce

From log pi to pi: Taming Divergence in Soft Clipping via Bilateral Decoupled Decay of Probability Gradient Weight

arXiv:2603.14389v2 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has catalyzed a leap in Large Language Model (LLM) reasoning, yet its optimization dynamics re

Functional Similarity Metric for Neural Networks: Overcoming Parametric Ambiguity via Activation Region Analysis

arXiv:2604.16426v1 Announce Type: new Abstract: As modern deep learning architectures grow in complexity, representational ambiguity emerges as a critical barrier to their interpretability and reliabl

Fuzzy Encoding-Decoding to Improve Spiking Q-Learning Performance in Autonomous Driving

arXiv:2604.16436v1 Announce Type: cross Abstract: This paper develops an end-to-end fuzzy encoder-decoder architecture for enhancing vision-based multi-modal deep spiking Q-networks in autonomous driv

Generalizable Face Forgery Detection via Separable Prompt Learning

arXiv:2604.17307v1 Announce Type: new Abstract: Detecting face forgeries using CLIP has recently emerged as a promising and increasingly popular research direction. Owing to its rich visual knowledge

Generalization Boundaries of Fine-Tuned Small Language Models for Graph Structural Inference

arXiv:2604.18092v1 Announce Type: new Abstract: Small language models fine-tuned for graph property estimation have demonstrated strong in-distribution performance, yet their generalization capabiliti

GeoRC: A Benchmark for Geolocation Reasoning Chains

arXiv:2601.21278v2 Announce Type: replace-cross Abstract: Vision Language Models (VLMs) are good at recognizing the global location of a photograph -- their geolocation prediction accuracy rivals the

Google Cloud Next 2026 preview: The real story isn’t AI — it’s the control plane

model-releasessiliconangle

Everyone heading into Google Cloud Next this week is bracing for another wave of artificial intelligence announcements. More Gemini. More agents. More benchmarks. More onstage demos that look great in