model releases

Ajar: Measuring Open Privilege in Agent Defenses

arXiv:2609.26900v1 Announce Type: cross Abstract: A language model agent acts through the tools it is given. The data it reads while working on a task can redirect what it does with those tools. A gro

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Alignment Inertia: Auditing the Durability of Training Data Influence Through Policy Override Resistance

DGX agent

arXiv:2609.27333v1 Announce Type: new Abstract: Platform operators increasingly rely on system prompts and fine-tuning to govern model behavior, yet it remains unclear how reliably these interventions

model-releasesarxiv-cs-ai

24 Sept 2026

Amplify: A Lightweight Library for Reproducible Nonlinear Programming Problems in Robotics

model-releasesarxiv-cs-ro

arXiv:2609.28377v1 Announce Type: new Abstract: Optimization problems (OPs) are key to solving many challenging research problems in robotics. However, reproducibility still remains a major issue. In

An Adaptive Machine Learning Framework for Fluid Flow in Dual-Network Porous Media

arXiv:2603.19561v2 Announce Type: replace-cross Abstract: Porous materials -- natural or engineered -- often exhibit dual pore-network structures that govern processes such as mineral exploration and

An open benchmark for machine learning-based polymer property prediction

arXiv:2609.27036v1 Announce Type: cross Abstract: Polymer property prediction lacks open, standardized benchmarks that enable rigorous comparison of machine-learning methods, with existing resources c

An Open Pipeline and Dashboard for Systemic-Risk Evidence under the EU AI Act's Code of Practice

arXiv:2609.28335v1 Announce Type: new Abstract: Claims about AI safety reach audiences well beyond the AI community, yet many rely on opaque evidence or static assessments, when supporting evidence is

Anomaly-Free Self-Optimization via AUC Bounds

arXiv:2609.27362v1 Announce Type: new Abstract: Anomalies are rare, and anomalous data are often unavailable during development, making it difficult to determine which anomaly detection models and con

Anthropic says it made Claude.ai and the Claude desktop app's core UX ~3x faster in August using an internal model to ship improvements 'in a two-week sprint' (Anthropic)

Anthropic: Anthropic says it made Claude.ai and the Claude desktop app's core UX ~3x faster in August using an internal model to ship improvements “in a two-week sprint” — Once Claude can measure some

model-releasestechmeme

AraGenre 2026: A Hierarchical Definition-Guided Arabic Genre Classification Shared Task

arXiv:2609.27387v1 Announce Type: new Abstract: AraGenre is a shared task on hierarchical, definition-guided Arabic genre classification, motivated by the limited availability of annotated data in Ara

ASCIIBench: Evaluating Language-Model-Based Understanding of Visually-Oriented Text

arXiv:2512.04125v2 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated several emergent behaviors with scale, including reasoning and fluency in long-form text generation.

Ask Which, Not How Good: Sizing Benchmarks Scored by an LLM

arXiv:2609.27787v1 Announce Type: new Abstract: Benchmarks scored by an LLM judge routinely adjudicate differences of a tenth of a point, but the resolution of those benchmarks has never been measured

AstraLOD3: Zero-shot multimodal agentic reconstruction of LOD3 building models

arXiv:2609.28061v1 Announce Type: new Abstract: Automated LOD3 building modeling typically relies on purpose-built geometric or learning-based pipelines, limiting flexibility across heterogeneous buil

Automated Extraction of Records of Processing Activities (RoPA) Using Hybrid RAG and Locally Deployed Large Language Models

arXiv:2609.27359v1 Announce Type: new Abstract: Vietnam's Personal Data Protection Law (Law No. 91/2025/QH15) and Decree No. 356/2025/ND-CP, effective January 1, 2026, require organizations to establi

b11153

hexagon: reject MUL_MAT_ID when src1 precision is F32 (#29348) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/49757881 macOS/iOS: macOS Apple Silicon (arm6

b11154

test-save-load-state : print a per-model results table in --models mode (#29316) test-save-load-state : print a per-model results table in --models mode in --models mode the output was very heavy: eve

b11155

server,common : fix the GCC 12 stringop-overread false positive (again) (#29325) Signed-off-by: Adrien Gallouët angt@huggingface.co Website: https://llama.app Attestations: https://github.com/ggml-org

b11156

model : add Ling 3.0 VL support (#29151) model : fold Ling 3.0 VL into the BailingMoeV3 architecture Assisted-by: Scout model : keep shared NORM rope list intact when gating bailingmoe3 on mrope secti

b11157

cuda : add conv3d with implicit GEMM (#29137) cuda : add conv3d with implicit GEMM cuda : refine conv3d implicit GEMM and handle empty kernels Website: https://llama.app Attestations: https://github.c

b11158

vulkan: tune KHR cooperative matrix support for Adreno GPUs (#29328) Enable coopmat support for Vulkan backend Fixed the mul_mat_s Removed the debug statement Website: https://llama.app Attestations:

b11159

vulkan: handle misalignment in conv_2d and conv_3d (#29365) vulkan: handle misalignment in conv_2d and conv_3d fix test-backend-ops print Website: https://llama.app Attestations: https://github.com/gg

b11160

vulkan: int8 coopmat1 matmul implementation for AMD RDNA3 and RDNA4 (#27952) vulkan: add int8 coopmat quantized matmul shader apply scales inline use scalar sums probe and directly access coopmat valu

b11163

llama: add llama_batch_ext (#24669) (wip) add llama_batch_ext wip updated design updated impl change signature unused var demo common_prompt_batch_decode fix pos tmp disable test-batch-alloc fix compa

b11165

test: flush status (#28352) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/49978694 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, Klei

b11166

cuda : add F16 kernel support for CONV_2D_DW (#29064) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/49985945 macOS/iOS: macOS Apple Silicon (arm64) macOS

b11167

hexagon: support I32 CPY and CONT (#29379) Assisted-by: OpenCode Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/49994729 macOS/iOS: macOS Apple Silicon (ar

b11168

hexagon: dynamic quantizer improvements (#29395) hexagon: fix accuracy issue in Q8_0 N=1 MUL_MAT hex-quant: fix register spills hex-mm: use dma for all dyn.quant paths Co-authored-by: Aparna M P aparm

b11169

llama-grammar: fix numeric truncation for token_id parsing (#29382) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/50007794 macOS/iOS: macOS Apple Silicon

b11170

hexagon: handle multi-sequence in concat_2d (#29344) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/50014220 macOS/iOS: macOS Apple Silicon (arm64) macOS A

b11171

sync : ggml (#29396) ggml : bump version to 0.25.2 (ggml/1642) ggml : fix ubsan error in ggml_graph_nbytes (ggml/1644) ggml : bump version to 0.25.3 (ggml/1645) sync : ggml Website: https://llama.app

b11172

metal : optimize sparse FA + clean-up (#29377) metal : cache sparse FA indices in shared memory Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-Vision-Exp metal : simplify shared memory size calculation A

benched

benched 5.5 is IN-SANE. It almost broke our benchmark. I thought it was a bug. Claude Opus 5.5 is the new #1 on our writing benchmark, and it is not close at all. 2631 Elo. Second one, Fable, is at 23

model-releasesswyx--x

Benchmarking Active Spot Selection for Cost-Efficient Spatial Transcriptomics

arXiv:2609.27208v1 Announce Type: new Abstract: Spatial transcriptomics (ST) measures gene expression in tissue context, but dense capture grids can be costly and may repeatedly sample morphologically

Benchmarking Hyperspectral Foundation Models for Hyperspectral Unmixing

arXiv:2609.28283v1 Announce Type: new Abstract: Several foundation models dedicated to hyperspectral images have recently been made available. These models are trained on large unlabeled datasets and

Benchmarking Text-to-SQL under Role-Based Access Control

arXiv:2607.22115v2 Announce Type: replace-cross Abstract: Given a database S and a natural language question Q, text-to-SQL systems aim to generate an SQL query that correctly answers Q when executed

Beyond Balanced Accuracy: A Resolution and Parity-Controlled Benchmark for Vision-Language and Vision-Only Defect Assessment in UAV Power-Line Inspection

arXiv:2609.27457v1 Announce Type: new Abstract: Vision-language models (VLMs) are often reported to outperform task-specific vision backbones for unmanned aerial vehicle (UAV) power-line defect assess

Beyond Overlap: Estimating the Causal Effect of Benchmark Exposure

arXiv:2609.27176v1 Announce Type: new Abstract: Evidence that evaluation material entered training does not reveal how much it affected evaluation. This distinction leaves a contaminated benchmark sco

Beyond Poetry: Can Large Language Models Generate Classical Arabic Maqamat?

arXiv:2609.28245v1 Announce Type: cross Abstract: Large language models (LLMs) have shown strong performance in creative text generation, yet their ability to produce culturally grounded and stylistic

Beyond the Illusion of Power: Calibrating Quasi-Experiments in Observational IS

arXiv:2609.27299v1 Announce Type: cross Abstract: Information systems (IS) researchers increasingly use quasi-experimental methods such as difference-in-differences (DiD) and instrumental variables (I

BiCFlow-MER: Orchestrating Discriminative and Generative Multimodal Emotion Recognition via Conditional Transport

arXiv:2609.27615v1 Announce Type: new Abstract: In multimodal emotion recognition (MER), human affective states are inferred by integrating complementary cues from multiple modalities. In audio-text M

Binary Quantized Neural Network Training Is W[1]-Hard Parameterized by Input and Output Dimensions

arXiv:2609.27932v1 Announce Type: new Abstract: Ganian et al. (ICLR 2026) proved that quantized neural network training is fixed-parameter tractable when parameterized jointly by architecture treewidt

BranchDrive: A Branch-Structured Dataset for Action-Conditioned Driving Prediction

model-releasesarxiv-cs-ro

arXiv:2609.27275v1 Announce Type: new Abstract: Most autonomous-driving datasets record only the action executed by a behavior policy and the single future that followed, providing limited supervision

Calling it “X”

model-releasesanthropic--x

Mina Kimes posted that, despite facing backlash ('got cancelled'), she remains convinced that X (formerly Twitter) has returned to prominence. She characterizes the platform as the primary venue for i

Can Jev Judge Radiology Reports? Evaluating a System One Model for Clinical Factuality

arXiv:2609.27607v1 Announce Type: cross Abstract: An AI-generated radiology report can resemble a physician's report while omitting an abnormality, adding an unsupported finding, or reversing its pres

Can LLMs Catch a Rigged Backtest? A Clean-Control Calibration Benchmark

arXiv:2609.28090v1 Announce Type: cross Abstract: Backtest auditing is a calibration problem: high flaw recall is not useful when the model falsely flags matched clean strategies. We build a 96-item p

Can LLMs Reason About Runtime Behavior? A Repository-Level Dynamic Benchmark

arXiv:2609.28449v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in coding tasks, but their ability to reason about code execution remains unclear. Existing reposit

Can One Adapted Model Do It All? Fine-Tuning Strategy Selection for Customer Support LLMs

arXiv:2609.27262v1 Announce Type: new Abstract: Production customer-support systems often require LLMs to support multiple skills, such as intent classification, question answering, summarization, or

Can Vision-Language Models Analyze Human-Centered Video? Mapping Model Capabilities and Human-AI Collaborative Workflows

arXiv:2609.27327v1 Announce Type: new Abstract: Video provides a rich record of human behavior, interaction, and situated contexts, offering important evidence for understanding people and conducting

Causal Tracing of Audio-Text Fusion in Large Audio Language Models

arXiv:2603.13768v2 Announce Type: replace-cross Abstract: Despite the strong performance of large audio language models (LALMs) in various tasks, exactly how and where they integrate acoustic features