Search: “model-releases”

ODYN: An All-Shifted Non-Interior-Point Method for Quadratic Programming in Robotics and AI

arXiv:2602.16005v2 Announce Type: replace-cross Abstract: We introduce ODYN, a novel all-shifted primal-dual non-interior-point quadratic programming (QP) solver designed to efficiently handle challen

Model Releases

OmniTabBench: Mapping the Empirical Frontiers of GBDTs, Neural Networks, and Foundation Models for Tabular Data at Scale

DGX agent

arXiv:2604.06814v1 Announce Type: cross Abstract: While traditional tree-based ensemble methods have long dominated tabular tasks, deep neural networks and emerging foundation models have challenged t

model-releasesarxiv-cs-ai

10 Apr 2026

On Emotion-Sensitive Decision Making of Small Language Model Agents

arXiv:2604.06562v1 Announce Type: new Abstract: Small language models (SLM) are increasingly used as interactive decision-making agents, yet most decision-oriented evaluations ignore emotion as a caus

On Integrating Resilience and Human Oversight into LLM-Assisted Modeling Workflows for Digital Twins

arXiv:2603.25898v2 Announce Type: replace-cross Abstract: LLM-assisted modeling holds the potential to rapidly build executable Digital Twins of complex systems from only coarse descriptions and senso

On-Policy Distillation of Language Models for Autonomous Vehicle Motion Planning

model-releasesarxiv-cs-ro

arXiv:2604.07944v1 Announce Type: new Abstract: Large language models (LLMs) have recently demonstrated strong potential for autonomous vehicle motion planning by reformulating trajectory prediction a

Open-Ended Instruction Realization with LLM-Enabled Multi-Planner Scheduling in Autonomous Vehicles

arXiv:2604.08031v1 Announce Type: cross Abstract: Most Human-Machine Interaction (HMI) research overlooks the maneuvering needs of passengers in autonomous driving (AD). Natural language offers an int

Optimal Rates for Pure {arepsilon}-Differentially Private Stochastic Convex Optimization with Heavy Tails

arXiv:2604.06492v1 Announce Type: new Abstract: We study stochastic convex optimization (SCO) with heavy-tailed gradients under pure epsilon-differential privacy (DP). Instead of assuming a bound on t

Orion-Lite: Distilling LLM Reasoning into Efficient Vision-Only Driving Models

arXiv:2604.08266v1 Announce Type: new Abstract: Leveraging the general world knowledge of Large Language Models (LLMs) holds significant promise for improving the ability of autonomous driving systems

oslash Source Models Leak What They Shouldn't nrightarrow: Unlearning Zero-Shot Transfer in Domain Adaptation Through Adversarial Optimization

arXiv:2604.08238v1 Announce Type: new Abstract: The increasing adaptation of vision models across domains, such as satellite imagery and medical scans, has raised an emerging privacy risk: models may

Our first successful Gemma 4 Runtime in London with @swyx @patloeber @nick_kango @cormacb and others! 💎Great to go out for a run and talk a…

Our first successful Gemma 4 Runtime in London with @swyx @patloeber @nick_kango @cormacb and others! 💎Great to go out for a run and talk about Gemma, agents, evals and more @osanseviero @swyx and oth

model-releasesswyx--x

ParseBench: A Document Parsing Benchmark for AI Agents

arXiv:2604.08538v1 Announce Type: new Abstract: AI agents are changing the requirements for document parsing. What matters is semantic correctness: parsed output must preserve the structure and

PASK: Toward Intent-Aware Proactive Agents with Long-Term Memory

arXiv:2604.08000v1 Announce Type: cross Abstract: Proactivity is a core expectation for AGI. Prior work remains largely confined to laboratory settings, leaving a clear gap in real-world proactive age

PeReGrINE: Evaluating Personalized Review Fidelity with User Item Graph Context

arXiv:2604.07788v1 Announce Type: cross Abstract: We introduce PeReGrINE, a benchmark and evaluation framework for personalized review generation grounded in graph-structured user--item evidence. PeRe

Personalized RewardBench: Evaluating Reward Models with Human Aligned Personalization

arXiv:2604.07343v1 Announce Type: cross Abstract: Pluralistic alignment has emerged as a critical frontier in the development of Large Language Models (LLMs), with reward models (RMs) serving as a cen

PhyAVBench: A Challenging Audio Physics-Sensitivity Benchmark for Physically Grounded Text-to-Audio-Video Generation

arXiv:2512.23994v3 Announce Type: replace-cross Abstract: Text-to-audio-video (T2AV) generation is central to applications such as filmmaking and world modeling. However, current models often fail to

PhyEdit: Towards Real-World Object Manipulation via Physically-Grounded Image Editing

arXiv:2604.07230v2 Announce Type: replace Abstract: Achieving physically accurate object manipulation in image editing is essential for its potential applications in interactive world models. However,

Physical Knot Classification Beyond Accuracy: A Benchmark and Diagnostic Study

arXiv:2603.23286v3 Announce Type: replace Abstract: Physical knot classification is a fine-grained task in which the intended cue is rope crossing structure, but high accuracy may still come from appe

Physics-Informed Functional Link Constrained Framework with Domain Mapping for Solving Bending Analysis of an Exponentially Loaded Perforated Beam

arXiv:2604.07025v1 Announce Type: cross Abstract: This article presents a novel and comprehensive approach for analyzing bending behavior of the tapered perforated beam under an exponential load. The

Physics-Informed Neural Networks for Joint Source and Parameter Estimation in Advection-Diffusion Equations

arXiv:2512.07755v3 Announce Type: replace-cross Abstract: Recent studies have demonstrated the success of deep learning in solving forward and inverse problems in engineering and scientific computing

PIKA: Expert-Level Synthetic Datasets for Post-Training Alignment from Scratch

arXiv:2510.06670v2 Announce Type: replace Abstract: High-quality instruction data is critical for LLM alignment, yet existing open-source datasets often lack efficiency, requiring hundreds of thousand

Pinecone now has a native extension for Gemini CLI. gemini extensions install https://github.com/pinecone-io/gemini-cli-extension → 9 MCP to…

model-releasespinecone--x

Pinecone now has a native extension for Gemini CLI. gemini extensions install https://github.com/pinecone-io/gemini-cli-extension → 9 MCP tools → 7 skills (quickstart, query, assistant, RAG and more)

Pistachio: Towards Synthetic, Balanced, and Long-Form Video Anomaly Benchmarks

arXiv:2511.19474v4 Announce Type: replace-cross Abstract: Automatically detecting abnormal events in videos is crucial for modern autonomous systems, yet existing Video Anomaly Detection (VAD) benchma

Plasma GraphRAG: Physics-Grounded Parameter Selection for Gyrokinetic Simulations

arXiv:2604.06279v1 Announce Type: cross Abstract: Accurate parameter selection is fundamental to gyrokinetic plasma simulations, yet current practices rely heavily on manual literature reviews, leadin

PLUME: Latent Reasoning Based Universal Multimodal Embedding

arXiv:2604.02073v2 Announce Type: replace Abstract: Universal multimodal embedding (UME) maps heterogeneous inputs into a shared retrieval space with a single model. Recent approaches improve UME by g

PokeGym: A Visually-Driven Long-Horizon Benchmark for Vision-Language Models

arXiv:2604.08340v1 Announce Type: new Abstract: While Vision-Language Models (VLMs) have achieved remarkable progress in static visual understanding, their deployment in complex 3D embodied environmen

PrivFedTalk: Privacy-Aware Federated Diffusion with Identity-Stable Adapters for Personalized Talking-Head Generation

arXiv:2604.08037v1 Announce Type: cross Abstract: Talking-head generation has advanced rapidly with diffusion-based generative models, but training usually depends on centralized face-video and speech

Prompt reinforcing for long-term planning of large language models

arXiv:2510.05921v2 Announce Type: replace Abstract: Large language models (LLMs) have achieved remarkable success in a wide range of natural language processing tasks and can be adapted through prompt

Prune-Quantize-Distill: An Ordered Pipeline for Efficient Neural Network Compression

arXiv:2604.04988v1 Announce Type: cross Abstract: Modern deployment often requires trading accuracy for efficiency under tight CPU and memory constraints, yet common compression proxies such as parame

PSR: Scaling Multi-Subject Personalized Image Generation with Pairwise Subject-Consistency Rewards

arXiv:2512.01236v2 Announce Type: replace Abstract: Personalized generation models for a single subject have demonstrated remarkable effectiveness, highlighting their significant potential. However, w

PULSE: Privileged Knowledge Transfer from Rich to Deployable Sensors for Embodied Multi-Sensory Learning

arXiv:2510.24058v2 Announce Type: replace-cross Abstract: Multi-sensory systems for embodied intelligence, from wearable body-sensor networks to instrumented robotic platforms, routinely face a sensor

Q-Probe: Scaling Image Quality Assessment to High Resolution via Context-Aware Agentic Probing

arXiv:2601.15356v4 Announce Type: replace-cross Abstract: Reinforcement Learning (RL) has empowered Multimodal Large Language Models (MLLMs) to achieve superior human preference alignment in Image Qua

QNAS: A Neural Architecture Search Framework for Accurate and Efficient Quantum Neural Networks

arXiv:2604.07013v1 Announce Type: cross Abstract: Designing quantum neural networks (QNNs) that are both accurate and deployable on NISQ hardware is challenging. Handcrafted ansatze must balance expre

Quantitative Estimation of Target Task Performance from Unsupervised Pretext Task in Semi/Self-Supervised Learning

arXiv:2508.07299v2 Announce Type: replace-cross Abstract: The effectiveness of unlabeled data in Semi/Self-Supervised Learning (SSL) depends on appropriate assumptions for specific scenarios, thereby

Quantum-Inspired Tensor Network Autoencoders for Anomaly Detection: A MERA-Based Approach

arXiv:2604.06541v1 Announce Type: cross Abstract: We investigate whether a multiscale tensor-network architecture can provide a useful inductive bias for reconstruction-based anomaly detection in coll

QueryData helps agents turn natural language into queries for AlloyDB, Cloud SQL and Spanner

model-releasesgoogle-cloud-ai

QueryData launches in preview today. It is a tool for translating natural language into database queries with near-100% accuracy. With QueryData, you can build agentic experiences across AlloyDB, Clou

🚀 Qwen Code v0.14.0 – v0.14.2 are now available Channels：Control Qwen Code remotely from Telegram, DingTalk, or WeChat — send a message fro…

🚀 Qwen Code v0.14.0 – v0.14.2 are now available Channels：Control Qwen Code remotely from Telegram, DingTalk, or WeChat — send a message from your phone, get results on your server Cron Jobs ：Schedule

model-releasesqwen--x

Raising the security baseline: Essential AI and cloud security now on by default

model-releasesgoogle-cloud-ai

The rapid evolution of AI is redefining industries, while also exposing organizations to new risks. At Google Cloud, we believe that modern cloud defense should have AI protection built in and accessi

Reinforcement-Guided Synthetic Data Generation for Privacy-Sensitive Identity Recognition

arXiv:2604.07884v1 Announce Type: new Abstract: High-fidelity generative models are increasingly needed in privacy-sensitive scenarios, where access to data is severely restricted due to regulatory an

Replacing Tunable Parameters in Weather and Climate Models with State-Dependent Functions using Reinforcement Learning

arXiv:2601.04268v2 Announce Type: replace Abstract: Weather and climate models rely on parametrisations to represent unresolved sub-grid processes. Traditional schemes rely on fixed coefficients that

Restoring Heterogeneity in LLM-based Social Simulation: An Audience Segmentation Approach

arXiv:2604.06663v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used to simulate social attitudes and behaviors, offering scalable 'silicon samples' that can approximat

Rethinking Entropy Allocation in LLM-based ASR: Understanding the Dynamics between Speech Encoders and LLMs

arXiv:2604.08003v1 Announce Type: cross Abstract: Integrating large language models (LLMs) into automatic speech recognition (ASR) has become a dominant paradigm. Although recent LLM-based ASR models

REVEAL: Reasoning-Enhanced Forensic Evidence Analysis for Explainable AI-Generated Image Detection

arXiv:2511.23158v2 Announce Type: replace-cross Abstract: The rapid progress of visual generative models has made AI-generated images increasingly difficult to distinguish from authentic ones, posing

Revisiting Radar Perception With Spectral Point Clouds

arXiv:2604.08282v1 Announce Type: new Abstract: Radar perception models are trained with different inputs, from range-Doppler spectra to sparse point clouds. Dense spectra are assumed to outperform sp

Riemann-Bench: A Benchmark for Moonshot Mathematics

arXiv:2604.06802v1 Announce Type: new Abstract: Recent AI systems have achieved gold-medal-level performance on the International Mathematical Olympiad, demonstrating remarkable proficiency at competi

Robust support vector model based on bounded asymmetric elastic net loss for binary classification

arXiv:2603.06257v2 Announce Type: replace-cross Abstract: In this paper, we propose a novel bounded asymmetric elastic net (L_{baen}) loss function and combine it with the support vector machine (SV

Robustness Risk of Conversational Retrieval: Identifying and Mitigating Noise Sensitivity in Qwen3-Embedding Model

arXiv:2604.06176v1 Announce Type: cross Abstract: We present an empirical study of embedding-based retrieval under realistic conversational settings, where queries are short, dialogue-like, and weakly

SALLIE: Safeguarding Against Latent Language & Image Exploits

arXiv:2604.06247v1 Announce Type: cross Abstract: Large Language Models (LLMs) and Vision-Language Models (VLMs) remain highly vulnerable to textual and visual jailbreaks, as well as prompt injections

SANDO: Safe Autonomous Trajectory Planning for Dynamic Unknown Environments

model-releasesarxiv-cs-ro

arXiv:2604.07599v1 Announce Type: new Abstract: SANDO is a safe trajectory planner for 3D dynamic unknown environments, where obstacle locations and motions are unknown a priori and a collision-free p