model releases

Neuro-symbolic Syntactic Parsing: Shaping a Neural Network with the CYK Algorithm

arXiv:2605.31421v1 Announce Type: cross Abstract: In this paper, we show the possibility of a direct injection of algorithms into neural network architecture. We focus on a complex algorithm, that is,

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NGDBench: Towards Neural Graph Data Management

DGX agent

arXiv:2603.05529v2 Announce Type: replace-cross Abstract: Data critical to real-world decision-making is increasingly found within organizations. Such data is heterogeneous, constantly evolving, and o

model-releasesarxiv-cs-ai

1 Jun 2026

Not All Synthetic Data Is Yours to Learn From

arXiv:2605.31126v1 Announce Type: cross Abstract: Can a language model improve from plain text sampled from itself, with no prompts, no teacher, no verifier, and no reward model? Yes, but only when th

nuReasoning: A Reasoning-Centric Dataset and Benchmark for Long-Tail Autonomous Driving

arXiv:2605.31572v1 Announce Type: new Abstract: Reasoning is essential for autonomous driving (AD) in long-tail scenarios, where vehicles must apply commonsense knowledge, understand spatial relations

Nvidia launches Nemotron 3 Ultra, a 550B-parameter MoE open model; Artificial Analysis: it's the smartest open US model but trails the Chinese model Kimi K2.6 (Maximilian Schreiner/The Decoder)

Maximilian Schreiner / The Decoder: Nvidia launches Nemotron 3 Ultra, a 550B-parameter MoE open model; Artificial Analysis: it's the smartest open US model but trails the Chinese model Kimi K2.6 — It

model-releasestechmeme

OBCache: Optimal Brain KV Cache Pruning for Efficient Long-Context LLM Inference

arXiv:2510.07651v2 Announce Type: replace-cross Abstract: Large language models (LLMs) with extended context windows enable powerful applications but impose significant memory overhead, as caching all

Omni-Supervised Motion Editing: Balancing Change and Invariance through Positive-Negative Learning

arXiv:2605.30969v1 Announce Type: new Abstract: Text-based human motion editing aims to modify existing motion sequences according to natural language instructions while maintaining the consistency of

On-Device Generative AI for GDPR-Compliant Visual Monitoring: Natural Language Alerts from Local Object Detection

arXiv:2605.30544v1 Announce Type: new Abstract: Visual monitoring systems that rely on cloud-based AI inference expose raw image data to external services, creating fundamental tensions with the data-

On the Robustness of Multilingual Text Embedding Rankings Across Learning Tasks, Languages, and Benchmark Datasets

arXiv:2605.31142v1 Announce Type: cross Abstract: Large-scale multilingual text embedding models play crucial role in both research and industry, yet their behavior in language-specific, multi-task se

One of the big reasons for the current lack of patriotism and pride in our nation’s history is that about 40 years ago our most prominent st…

model-releaseselon-musk--x

One of the big reasons for the current lack of patriotism and pride in our nation’s history is that about 40 years ago our most prominent storytellers in Hollywood just basically stopped telling stori

One of the new, buzzy jobs in Silicon Valley is the AI Forward Deployed Engineer (FDE), an engineer who is embedded within a client organiza…

model-releasesandrew-ng--x

One of the new, buzzy jobs in Silicon Valley is the AI Forward Deployed Engineer (FDE), an engineer who is embedded within a client organization to help customize solutions, such as building and tunin

OpenAI frontier models and Codex are now generally available on AWS, giving enterprises a new way to build on Amazon Bedrock with OpenAI thr…

OpenAI frontier models and Codex are now generally available on AWS, giving enterprises a new way to build on Amazon Bedrock with OpenAI through the security, compliance, and governance workflows they

model-releasesopenai--x

OpenAI models and Codex on Amazon Bedrock are now generally available

model-releasesaws-ml-blog

OpenAI frontier models GPT-5.5 and GPT-5.4, and Codex, the OpenAI coding agent, are now generally available on Amazon Bedrock. AWS customers can access these latest OpenAI models through the same Amaz

Pairwise Reference Alignment as a Model-Level Ordinal Observable

arXiv:2605.30758v1 Announce Type: new Abstract: Pairwise preference data is widely used in language-model evaluation and alignment, often for model ranking, reward modeling, or preference optimization

Palo Alto Networks says Mythos found 24+ critical bugs using $1M+ in tokens; Anthropic subsidizes Mythos but some companies plan to boost their Mythos budgets (Aaron Holmes/The Information)

Aaron Holmes / The Information: Palo Alto Networks says Mythos found 24+ critical bugs using $1M+ in tokens; Anthropic subsidizes Mythos but some companies plan to boost their Mythos budgets — When Pa

model-releasestechmeme

Parameter-free Dynamic Regret: Time-varying Movement Costs, Delayed Feedback, and Memory

arXiv:2602.06902v2 Announce Type: replace Abstract: In this paper, we study dynamic regret in unconstrained online convex optimization (OCO) with movement costs. Specifically, we generalize the standa

PhyDrawGen: Physically Grounded Diagram Generation from Natural Language

arXiv:2605.30512v1 Announce Type: new Abstract: Generating physics diagrams from text requires strict adherence to physical laws. While current generative models produce visually plausible outputs, th

Physically Viable World Models: A Case for Query-Conditioned Embodied AI

arXiv:2605.30542v1 Announce Type: new Abstract: World models for embodied AI must be physically viable: constructed to answer intervention queries by representing the physical structure governing acti

Physics Enhanced Deep Surrogates for the Phonon Boltzmann Transport Equation

arXiv:2512.05976v3 Announce Type: replace-cross Abstract: Designing materials with controlled heat flow at the nano-scale is central to advances in microelectronics, thermoelectrics, and energy-conver

PInVerify: An Offline Embodied Benchmark for Active Instance Verification

arXiv:2605.30639v1 Announce Type: cross Abstract: Embodied agents have made strong progress in navigating to target objects, but reaching the goal vicinity does not guarantee that the agent has found

Plain Transformers are Surprisingly Powerful Link Predictors

arXiv:2602.01553v2 Announce Type: replace-cross Abstract: Link prediction is a core challenge in graph machine learning, demanding models that capture rich and complex topological dependencies. While

PRISM: Progressive Reasoning through Iterative Slot Memory for Vision

arXiv:2605.30942v1 Announce Type: new Abstract: Modern vision models process images in a single feed-forward pass, which limits their ability to recover missing evidence or refine uncertain representa

Probabilistic Precipitation Nowcasting with Rectified Flow Transformers

arXiv:2605.31204v1 Announce Type: new Abstract: Accurate weather forecasts are essential across various domains and are safety-critical in extreme weather conditions. Compared to simulation-based fore

Probing Collision Grounding in Vision-Language Models for Safe Human-Robot Collaboration

arXiv:2605.31196v1 Announce Type: cross Abstract: Safe human--robot collaboration requires more than visual description: a monitor must determine whether the robot body is safely separated, already co

Probing the Prompt KV Cache: Where It Becomes Dispensable

arXiv:2605.30574v1 Announce Type: new Abstract: Prior KV cache compression schemes empirically demonstrate that the prompt cache is partially redundant during decoding, dropping or summarising entries

QASM-Eval: A Dataset to Train and Evaluate LLMs on OpenQASM-3 Beyond Quantum Circuits

arXiv:2605.30358v1 Announce Type: new Abstract: Quantum computing remains in the Noisy Intermediate-Scale Quantum (NISQ) era, where the performance is highly constrained to noise. Addressing the limit

Quantifying the Uncertainty of Foundation Models with Singular Value Ensembles

arXiv:2601.22068v2 Announce Type: replace Abstract: Foundation models have become a dominant paradigm in machine learning, achieving remarkable performance across diverse tasks through large-scale pre

Query-focused and Memory-aware Reranker for Long Context Processing

arXiv:2602.12192v3 Announce Type: replace Abstract: Built upon the existing analysis of retrieval heads in large language models, we propose an alternative reranking framework that trains models to es

QVGGT: Post-Training Quantized Visual Geometry Grounded Transformer

arXiv:2605.31124v1 Announce Type: new Abstract: Estimating 3D attributes directly from images has advanced rapidly with the Visual Geometry Grounded Transformer (VGGT), which predicts camera parameter

Qwen 3.7 Plus now available on AI Gateway

model-releasesvercel-blog

Vercel has made Qwen 3.7 Plus, an AI model, available through its AI Gateway service, allowing developers to access this model via Vercel's platform. This addition expands the model options available

Randomized Feasibility Methods for Constrained Optimization with Adaptive Step Sizes

arXiv:2601.20076v2 Announce Type: replace-cross Abstract: We consider minimizing an objective function subject to constraints defined by the intersection of lower-level sets of convex functions. We st

Re-examining Low Rank adaptation for private LLM fine-tuning

arXiv:2510.01137v3 Announce Type: replace Abstract: Privacy is a central concern when fine-tuning large language models (LLMs) on sensitive data, and differentially private stochastic gradient descent

Recognizing Co-Speech Gestures in-the-Wild

arXiv:2605.31589v1 Announce Type: new Abstract: While humans naturally gesture during speech, only a sparse subset of these movements are visually depictive and semantically linked to specific spoken

ReTabAD: A Benchmark for Restoring Semantic Context in Tabular Anomaly Detection

arXiv:2510.02060v2 Announce Type: replace Abstract: In tabular anomaly detection (AD), textual semantics often carry critical signals, as the definition of an anomaly is closely tied to domain-specifi

SAEmnesia: Erasing Concepts in Diffusion Models with Supervised Sparse Autoencoders

arXiv:2509.21379v3 Announce Type: replace-cross Abstract: Concept unlearning in diffusion models is hampered by feature splitting, where concepts are distributed across many latent features, making th

Safe Equilibrium Policy Optimization for Strategic Agent Policies

arXiv:2605.30854v1 Announce Type: cross Abstract: Language models fine-tuned with reinforcement learning typically optimize for task reward, ignoring multi-agent strategic structure. Because these age

Same Patient, Different Words, Different Diagnosis? Evaluating Semantic Stability in Clinical LLMs

arXiv:2605.30646v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in clinical applications. However, their behavior remains highly sensitive to subtle linguistic var

SAW-Bench: Learning Situated Awareness in the Real World

arXiv:2602.16682v2 Announce Type: replace Abstract: A core aspect of human perception is situated awareness, the ability to relate ourselves to the surrounding physical environment and reason over pos

Scaling Conversational Hungarian ASR: The BEA-Dialogue+ Corpus

arXiv:2605.31469v1 Announce Type: cross Abstract: Conversational automatic speech recognition in Hungarian is constrained by the limited amount of publicly available dialogue-style training data. The

Scaling Multi-Hop Training Data via Graph-Constrained Path Selection

arXiv:2605.31238v1 Announce Type: new Abstract: Endowing large language models with compositional reasoning over specialized documents requires multi-hop training data at scale, where such data rarely

Self-Tuning Regularization for Image Scanning Microscopy

arXiv:2605.31426v1 Announce Type: cross Abstract: Image Scanning Microscopy (ISM) is a fluorescence imaging technique that combines detector-array acquisition and computational reconstruction to achie

Send a SCOUT First: Pre-hoc Reasoning for Adaptive Detector Allocation in Prompt-Injection Defense

arXiv:2605.30837v1 Announce Type: cross Abstract: Prompt-injection detectors are heterogeneous: each is strong on a different slice of attacks, and none is always reliable. Yet existing systems still

Sequential Least-Squares Estimators with Fast Randomized Sketching for Linear Statistical Models

arXiv:2509.06856v2 Announce Type: replace-cross Abstract: We propose a novel randomized framework for the estimation problem of large-scale linear statistical models, namely Sequential Least-Squares E

Sequential Subspace Noise Injection Prevents Accuracy Collapse in Certified Unlearning

arXiv:2601.05134v2 Announce Type: replace Abstract: Certified unlearning based on differential privacy offers strong guarantees but remains largely impractical: the noisy fine-tuning approaches propos

SERA: Soft-Verified Efficient Repository Agents

arXiv:2601.20789v3 Announce Type: replace Abstract: Open-weight coding agents should hold a fundamental advantage over closed-source systems because they can specialize to private codebases, encoding

SimulCost: A Cost-Aware Benchmark and Toolkit for Automating Physics Simulations with LLMs

arXiv:2603.20253v2 Announce Type: replace-cross Abstract: Evaluating LLM agents for scientific tasks has focused on token costs while ignoring tool-use costs like simulation time and experimental reso

Skill Availability and Presentation Granularity in Large-Language-Model Agents: A Controlled SkillsBench Study

arXiv:2605.31408v1 Announce Type: cross Abstract: Skill documents provide procedural knowledge to large-language-model agents at inference time. This article studies whether the presentation granulari