Search: “model-releases”

Efficiency Hallucination: Formalizing and Measuring Behavioral Calibration in LLM-Based Code Optimization

arXiv:2609.14839v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) into automated code optimization introduces a critical reliability risk we term the Efficiency Halluci

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Model Releases

Efficient On-Device Agents via Adaptive Context Management

DGX agent

arXiv:2511.03728v2 Announce Type: replace Abstract: On-device AI agents offer the potential for personalized, low-latency assistance, but their deployment is fundamentally constrained by limited memor

model-releasesarxiv-cs-ai

15 Sept 2026

Eigenvalue-Decomposition Cost Denoising as an Alternative to Predict-then-Optimize for Shortest-Path Problems

arXiv:2609.15111v1 Announce Type: cross Abstract: Predict-then-optimize methods such as Smart 'Predict, then Optimize' (SPO+) of Elmachtoub and Grigas (2022) learn a mapping from contextual features t

ELON MUSK: I saw some pretty funny jokes on 𝕏. One of them I saw was: 'Your girlfriend's a 10, but she's a benchmark maxxer.' 🤣

model-releaseselon-musk--x

ELON MUSK: I saw some pretty funny jokes on 𝕏. One of them I saw was: 'Your girlfriend's a 10, but she's a benchmark maxxer.' 🤣 Media All-In Summit: Elon Musk & Gwynne Shotwell -- AI Risks and Peer Re

EMCStereo: Attention-Enhanced Stereo Matching for Thin-Structure Depth Estimation with a Synthetic Tree-Branch Benchmark

arXiv:2609.13233v1 Announce Type: new Abstract: Thin structures such as tree branches are among the hardest cases for stereo matching: a branch is only a few pixels wide, the background is cluttered,

Empirical Evaluation of Open-Source Large Language Models for Retrieval-Augmented Generation in ESG Domain

arXiv:2609.15242v1 Announce Type: new Abstract: Environmental, Social, and Governance (ESG) reporting is critical for corporate accountability, with Large Language Models (LLMs) and Retrieval-Augmente

Empirical Evaluation of Task-Based Permission Scoping Architecture for AI Agents

arXiv:2609.15422v1 Announce Type: new Abstract: AI agents are provisioned the same as employee-owned hosts in many enterprise settings with a static credential set fixed at deployment which includes a

End-to-End Cell Detection via Instance-aware Graph Modeling

arXiv:2609.15354v1 Announce Type: cross Abstract: Accurate cell detection and classification are crucial for pathological analysis, directly affecting diagnostic accuracy and treatment planning. To ca

Enemray: Toward Capable Language Models for Hassaniya

arXiv:2609.14829v1 Announce Type: cross Abstract: We introduce Enemray, a Hassaniya-centric language model that enables general-purpose interaction in Hassaniya. Enemray is trained around a stability-

Enhancing Large Language Model-Based Systems for End-to-End Circuit Analysis Problem Solving

arXiv:2512.10159v3 Announce Type: replace-cross Abstract: LLMs have shown strong performance in data-rich domains such as programming, but their reliability in engineering tasks remains limited. Circu

ESG: Generating Physically Consistent Dynamic 3D Scenes from Text Descriptions

arXiv:2609.15392v1 Announce Type: cross Abstract: Recent progress in image and 3D scene generation has enabled increasingly realistic static environments, yet most methods remain confined to such stat

Evaluating Context Segmentation in Locally Deployable SLMs for Cybersecurity CTF Tasks

arXiv:2609.12839v2 Announce Type: replace-cross Abstract: The proliferation of highly capable open-weight Small Language Models (SLMs) democratizes access to advanced cybersecurity capabilities, posin

Evaluating Contextual Bias in CNN Image Classification: Evidence from Agricultural Benchmark Datasets

arXiv:2609.14654v1 Announce Type: new Abstract: Convolutional neural networks (CNNs) are typically evaluated using held-out classification accuracy, an approach that presupposes predictions are based

Evaluating LLM-Generated Rules for Heart Disease Prediction

arXiv:2609.13192v1 Announce Type: new Abstract: This study compares traditional machine learning models and Large Language Model (LLM)-generated rule-based systems for heart disease prediction using t

Evaluation of optimisation and Bayesian inference methods for reaction rates in atmospheric chemical mechanisms

arXiv:2609.14569v1 Announce Type: cross Abstract: Constraining reaction rate coefficients is a central challenge in the development of explicit atmospheric chemical mechanisms, particularly for autoxi

Exact Finite Attention Responses From RoPE Derivatives

arXiv:2609.14127v1 Announce Type: cross Abstract: We derive exact local responses for attention interventions, allowing candidate edits to be scored from a cached baseline and one backward pass. The s

Exploring Automated Vulnerability Identification in JavaScript Code Using Large Language Models

arXiv:2609.13816v1 Announce Type: cross Abstract: JavaScript powers approximately 98.8% of all websites, making vulnerabilities in its code a significant security risk, yet existing detection approach

Exploring new directions in enhancing the ACTS parameter optimization suite

arXiv:2608.14714v1 Announce Type: cross Abstract: Track seeding strongly affects both the quality and computational cost of charged-particle reconstruction, yet its many configuration parameters are c

Fabrication After Tool Failure: Tool-Augmented Agents Assert Values Their Tools Did Not Return

model-releasesarxiv-cs-cl

arXiv:2609.14758v1 Announce Type: cross Abstract: Tool-augmented language models are evaluated on whether they reach the right answer, not on whether they report honestly when a tool fails to supply o

FaithfulBench: Does AI Counsel Uphold or Undermine the User's Professed Faith?

arXiv:2609.13634v1 Announce Type: cross Abstract: Do AI assistants help believers reason about moral dilemmas consistently with their faith? We present FaithfulBench, the first benchmark to score AI c

FedLTLib: A Comprehensive Benchmark for Federated Long-Tail Learning

arXiv:2609.15625v1 Announce Type: cross Abstract: Driven by the escalating demand for privacy-preserving computing, Federated Learning (FL) has witnessed remarkable progress, becoming a cornerstone te

FedV-KGQA in Practice: Design Lessons and an Interactive Prototype

arXiv:2609.13661v1 Announce Type: new Abstract: Knowledge graph question answering usually assumes that one system can reach the whole graph. In practice, facts are often held by organizations that sh

FFVO: A Feedforward Pose Decoder for Long-Horizon Visual Odometry

arXiv:2609.13733v1 Announce Type: new Abstract: Stable and reliable 4D spatial understanding is fundamental for autonomous driving systems. While feedforward reconstruction networks can estimate camer

Finite-Time Node Separation in Recurrent Graph Neural Networks with Persistent Gaussian Perturbations

arXiv:2609.13920v1 Announce Type: cross Abstract: Persistent Gaussian perturbations have been shown to prevent asymptotic oversmoothing in recurrent Graph Neural Networks (GNNs) by ensuring a positive

FLoKD: Adaptive Knowledge Distillation for Federated Low-Rank LLM over Wireless Networks

arXiv:2609.13580v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong capabilities across a wide range of natural language processing tasks. However, conventional fine-

Floquet Fibre Geometry and Higher-Order Reduced Coordinates for Off-Manifold Transients near Nonlinear Aeroelastic Flutter

arXiv:2609.14674v1 Announce Type: new Abstract: Assigning reduced coordinates to states near an attracting limit cycle requires the correct invariant-fibre geometry. The classical first-order phase-is

FlowTSFM: Turning Encoder Depth into Quantile Transport

arXiv:2609.13640v1 Announce Type: new Abstract: Encoder-based time series foundation models (TSFMs) typically rely on deep stacks of independently parameterized Transformer layers, where only the fina

For Web game development, I swear Flash Next on Q2 is better than Gemini Flash 3.8

model-releasesr-localllama

One thing I love about both Qwen 3.8 27B and Flash Next is the effort it puts in to make a good product. It is the opposite of a lazy model and 'good enough' is never what aims to accomplish. It goes

Frame-Synchronous Hand Gesture Detection by Projected Winding Order

arXiv:2609.13269v1 Announce Type: new Abstract: Gesture recognition on video is normally posed as classification: label each frame, then act on the label. That is adequate for control, where a command

Freeze, Share, Shrink: Rethinking the Action Backbone in Diffusion Policies

arXiv:2511.12101v3 Announce Type: replace-cross Abstract: Many recent Vision-Language-Action models employ diffusion or flow-matching backbones with hundreds of millions of parameters for action gener

From Density to Biopsy Decisions and Malignancy Prediction: A Benchmark Study of Multimodal Large Language Models Against Radiologists in Digital and Contrast-Enhanced Mammography

arXiv:2609.14676v1 Announce Type: new Abstract: Purpose: To compare four multimodal large language models (MLLMs) with radiologists of varying expertise in breast density assessment, BI-RADS assessmen

From Refusal Tokens to Refusal Control: Discovering and Steering Category-Specific Refusal Directions

arXiv:2603.13359v2 Announce Type: replace Abstract: Language models are commonly fine-tuned for safety alignment to refuse harmful prompts. One approach fine-tunes them to generate categorical refusal

From Vision to Harvest: Benchmarking Vision-Language Models for Multi-Arm Robotic Fruit Harvesting

arXiv:2609.13606v1 Announce Type: cross Abstract: Multi-arm robotic harvesting offers a promising path to improve harvesting efficiency and reduce reliance on manual labor. However, practical deployme

Func-R1: Incentivizing Mathematical Function Reasoning in Multimodal Large Language Models

model-releasesarxiv-cs-cl

arXiv:2609.14779v1 Announce Type: new Abstract: Performing deliberate mathematical reasoning in visual contexts is a hallmark of advanced Multimodal Large Language Models (MLLMs) and requires a sophis

Fusing Spectral Signatures and Activation Clustering for Backdoor Detection in Healthcare Imaging Models: Method, Implementation, and Evaluation

arXiv:2609.14290v1 Announce Type: cross Abstract: Machine learning models are increasingly deployed in healthcare imaging pipelines for diagnostic support, and training-time attacks against them are a

Gemini 3.8 Live is rolling out to: — Consumers: in Search Live — Developers: in public preview in the Gemini API via @googleaistudio — Enter…

model-releasesgoogle-ai--x

Gemini 3.8 Live is rolling out to: — Consumers: in Search Live — Developers: in public preview in the Gemini API via @googleaistudio — Enterprises: in private preview via Gemini Enterprise (coming soo

Gemini Live audio

model-releasessimon-willison

Tool: Gemini Live audio Google released Gemini 3.8 Live and 3.8 Live Extended Thinking today - two new speech-to-speech models that are a similar shape to OpenAI's GPT-Live family. I pointed GPT-6 Ast

GGUF-Metadata Prediction of Single-Sequence llama.cpp Throughput Across Three Systems

arXiv:2609.14864v1 Announce Type: new Abstract: We predict single-sequence model throughput from GGUF metadata using roofline-shaped predictors with quantization-specific scale factors fitted on refer

Google gives all of its engineers Claude Opus 5 access via Antigravity, and says 'Gemini remains our primary and foundational model for internal development' (Hugh Langley/Business Insider)

Hugh Langley / Business Insider: Google gives all of its engineers Claude Opus 5 access via Antigravity, and says “Gemini remains our primary and foundational model for internal development” — Googler

model-releasestechmeme

Google’s new speech model Gemini 3.8 Live supports real-time reasoning

model-releasessiliconangle

Google LLC is trying to address the latency problem associated with voice-based artificial intelligence agents with the launch of Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking today. They’re b

GorillaWatch: An Automated System for In-the-Wild Gorilla Re-Identification and Population Monitoring

arXiv:2512.07776v2 Announce Type: replace Abstract: Monitoring critically endangered western lowland gorillas is currently hampered by the immense manual effort required to re-identify individuals fro

Gradient-Free Neural Hamilton-Jacobi Reachability for Scalable Safety-Critical Control

model-releasesarxiv-cs-ro

arXiv:2609.14087v1 Announce Type: new Abstract: Hamilton-Jacobi (HJ) reachability provides a principled framework for synthesizing safety certificates and robust controllers for safety-critical roboti

Graph-Transformer Fraud Detection with Self-Supervised Pretraining and Conformal Risk Control

arXiv:2609.14234v1 Announce Type: cross Abstract: Financial fraud in corporate transaction networks has grown more coordinated and harder to detect with rule-based engines and with classical learning

GRAVA: Grounded Reasoning-to-Action Representation and Learning for Autonomous Driving

arXiv:2609.15169v1 Announce Type: new Abstract: Driving vision-language-action (VLA) models increasingly reason before acting, but their intermediate reasoning is often weakly grounded in physical sce

GRIN+: Towards Fast Yet Effective Machine Unlearning for Imbalanced Medical Data

arXiv:2609.15571v1 Announce Type: new Abstract: As deep learning models become fundamental to modern healthcare, the 'Right to be Forgotten' mandated by privacy regulations like GDPR and HIPAA necessi

GROOVE: Geometry-Guided Reduction of Operational-Space Jerk in VLA Execution

model-releasesarxiv-cs-ro

arXiv:2609.13695v1 Announce Type: new Abstract: Chunked vision language action (VLA) policies execute several commands per query, but jerk within chunks and across replanning boundaries can induce osc

GroundBench: A Factorized, Counterfactual Benchmark for Locating VLM Affordance Failures

arXiv:2609.13308v1 Announce Type: new Abstract: A companion evaluation found that naming the target part in a manipulation prompt increased action accuracy by 0.32-0.63 across eight vision-language mo

Grounded Adjudication of Variations across Extracted TimeLines (GAVEL): Comparing Clinical Timelines Against Their Case Reports

arXiv:2609.13475v1 Announce Type: new Abstract: Existing pipelines for clinical timeline extraction from case reports are evaluated using an expert reference and are limited by imperfect reference ann