Search: “model-releases”

Geometric Parrots: Rule Absence vs. Rule Fragility in Spatial and Physical Reasoning for Vision-Language Models

arXiv:2610.16170v1 Announce Type: new Abstract: Vision-language models (VLMs) can answer many geometric and physical reasoning questions correctly, yet still behave inconsistently in interaction, for

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Model Releases

Geometry-Aware Predictive Control for Walk-to-Run Bipedal Obstacle Crossing

DGX agent

arXiv:2610.15735v1 Announce Type: new Abstract: This paper presents a geometry-aware predictive control framework for bipedal obstacle crossing across walking and running regimes. The proposed approac

model-releasesarxiv-cs-ro

14 Oct 2026

GeoReader: Learning Latent Geometry for Spatial Reasoning in Vision-Language Models

arXiv:2610.18694v1 Announce Type: new Abstract: Vision-language models (VLMs) struggle with metric and multi-view relationships that remain implicit in RGB observations. Geometry foundation models rec

GIFT-Eval-CTX: A Benchmark For Contextual Forecasting Model Evaluation

arXiv:2610.17794v1 Announce Type: new Abstract: Contextual forecasting seeks to improve time series forecasting by incorporating forward-looking information, such as planned events, external condition

GNFormer: Gaussian Neural Field Transformer for Efficient Camera-based Occupancy Prediction

arXiv:2610.15522v1 Announce Type: cross Abstract: Camera-based occupancy prediction provides geometric and semantic scene understanding for robot perception and has been adopted in autonomous vehicle

Google DeepMind and Singapore Government announce new AI tool to protect citizens against scams

model-releasesgoogle-deepmind

Google DeepMind and the Singapore Government have launched a partnership to deploy an artificial‑intelligence tool designed to help citizens identify and avoid scams. Announced in May 2026, the initia

GPU Goldmines: Tunable WebGPU Kernels for Edge LLM Inference

arXiv:2610.17321v1 Announce Type: cross Abstract: As demand for LLM inference grows and consumer GPUs grow more capable, edge deployment is becoming increasingly attractive. WebGPU is compelling in th

Grables: When Graph Structure Helps Tabular Prediction

arXiv:2602.03945v2 Announce Type: replace Abstract: Simple row-wise predictors that score each row independently remain competitive with far more expressive architectures on tabular benchmarks, which

GREAT: A Graph Edge Attention Network for the Electric Vehicle Routing Problem with Asymmetric Costs

arXiv:2408.16717v4 Announce Type: replace Abstract: Due to the ongoing electrification of transportation systems, energy-based routing problems such as the Electric Vehicle Routing Problem (EVRP) are

Groundcover lets Claude and Codex hand production investigations to its own agent

model-releasessiliconangle

Application observability startup groundcover Inc. today gave outside artificial intelligence coding agents such as Anthropic PBC’s Claude and OpenAI Group PBC’s Codex a way to hand production investi

Growing and Transferring Pathways for LLM Reinforcement Learning

arXiv:2610.16489v1 Announce Type: new Abstract: Reinforcement learning (RL) can substantially improve the reasoning capabilities of large language models, but an effective training run requires consid

GUARD: Guided Unlearning and Retention via Data Attribution for Large Language Models

arXiv:2506.10946v3 Announce Type: replace Abstract: Unlearning large language models (LLMs) is important due to copyright and privacy concerns. A key challenge is unintended forgetting, where removing

HALLMARK: How to Diagnose LLM Citation Verifiers and When to Deploy Them

arXiv:2607.18360v2 Announce Type: replace-cross Abstract: GPTZero found 53 NeurIPS 2025 accepted papers with hallucinated citations, and venues now screen submissions with automated reference checkers

Harmonic Representations in Symbolic Music Transformers are Localized and Controllable

arXiv:2610.15957v1 Announce Type: cross Abstract: Transformer models trained on symbolic music have become remarkably capable. However, it is yet unclear how they represent music structure, and whethe

Harness^2: Recursive Agent Harnessing for an Open World

arXiv:2610.14224v1 Announce Type: cross Abstract: LLM agents' capabilities depend not only on their underlying models but also on their execution harnesses. Recursive self-improvement (RSI) offers a p

HarnessTTT: Learn to Optimize Harness at Test-Time for Scientific Discovery

arXiv:2610.17370v1 Announce Type: new Abstract: Scientific discovery with language models requires finding the best valid solution within a finite computational budget. We study how feedback from this

Has anyone found a fix for Standard Voice Mode reading formatting, links and image data aloud

I've been using ChatGPT Voice for years, particularly during my commute to work. Until recently, I've almost exclusively used Standard Voice Mode, but a recent issue has made it practically unusable.

model-releasesr-chatgpt

HASTE: Hierarchical and Attribute-aware Supervision for Generative Recommendation

arXiv:2610.17368v1 Announce Type: cross Abstract: Generative recommendation models have shown promising results by representing items as semantic IDs and generating these IDs autoregressively. We intr

Heading Hierarchy Reconstruction for Complex and Long Documents with Level-Wise Multimodal Memory

arXiv:2610.18238v1 Announce Type: new Abstract: Vision-language models (VLMs) have been widely adopted for document parsing and optical character recognition (OCR), as they can accurately extract page

HelpMeOut: A Neuropsychology-Grounded Benchmark for Error-Aware Monitoring of Household Task Execution

arXiv:2610.17694v1 Announce Type: new Abstract: We introduce HelpMeOut, an embodied AI benchmark for error-aware monitoring of household task execution. Existing embodied household benchmarks typicall

Heterogeneous Structured Pruning Under Resource Constraints for Hardware-Efficient Large Language Models

arXiv:2610.15781v1 Announce Type: new Abstract: Training-free pruning removes weights from pretrained large language models to reduce their deployment cost. However, existing approaches typically cons

Hey, AI give me your best 'Unless it is from X, its just sparkling Y' style joke': GPT-6 Pro: 'Unless it comes from the Stockholm region of …

model-releasesethan-mollick--x

Hey, AI give me your best 'Unless it is from X, its just sparkling Y' style joke': GPT-6 Pro: 'Unless it comes from the Stockholm region of Sweden, it’s just sparkling employee engagement.' Gemini 4 A

Hierarchical Curriculum Learning for Surgical Video Generation: Focusing on Bilateral Axillo-Breast Approach Robotic Thyroidectomy Datasets

arXiv:2610.17684v1 Announce Type: new Abstract: High-fidelity surgical video generation is increasingly important for surgical education, simulation, and downstream AI training, as conventional simula

Historical Anchors for Scientific Forecasting on Human-Aware Knowledge Graphs

arXiv:2610.14023v1 Announce Type: new Abstract: Predicting which scientific connections will form next can point researchers toward the most promising leads. One successful approach learns representat

History, Adaptation, and Hidden Gain: Two Prospective Tests of Learned Predictive Control in a Synthetic Neural Population

arXiv:2610.14368v1 Announce Type: new Abstract: We study learned one-step predictive control of a synthetic population of 64 leaky integrate-and-fire neurons whose light sensitivity is scaled by a hid

Holistic Scaling Laws for Optimal Mixture-of-Experts Architecture Optimization

arXiv:2603.21862v2 Announce Type: replace Abstract: Scaling laws govern macroscopic resource allocation for LLMs, yet precise architectural configurations for Mixture-of-Experts (MoE) models remain gu

How Low Can You Go: Fine-Tuning LLMs with Bayesian Optimization (LlMBO)

arXiv:2610.18504v1 Announce Type: cross Abstract: Recently, Morris et al. introduced TinyLoRA, a strategy for LLM fine-tuning which introduces arbitrarily few parameters, and demonstrated accuracy imp

How the Classical Baseline Shapes Machine-Learning Speed Claims in Topology Optimization

arXiv:2610.16051v1 Announce Type: cross Abstract: Topology optimization places material so that a structure resists deformation under given loads. Machine-learning methods often report large speed-ups

How to Build a Benchmark That Actually Measures Taste

arXiv:2610.14707v1 Announce Type: cross Abstract: Expert-aligned 'taste' benchmarks should reward craft judgment, not the ability to game the test. We introduce TasteBench, a pairwise good-vs-bad benc

Human-Like Redundancy Resolution for Real-Time Bimanual Humanoid Teleoperation

arXiv:2610.16855v1 Announce Type: new Abstract: Real-time bimanual humanoid teleoperation requires accurate wrist tracking while keeping arm configurations predictable. Because a 7-DoF arm admits mult

HumanPhys: A Human-Centric Physical-World Perception Benchmark for Real-World Visual Reasoning

arXiv:2610.14679v1 Announce Type: new Abstract: We introduce HumanPhys, a human-centric benchmark for real-world physical perception, and a training corpus emitted by the same pipeline. Each question

HyBRA-EEG: Hyperbolic Global-Local Brain-Region Aggregation for Self-Supervised EEG Representation Learning

arXiv:2610.16589v1 Announce Type: new Abstract: Electroencephalography (EEG) representation learning is challenged by noisy signals, inter-subject variability, and heterogeneous electrode montages in

Hybrid Context Forests and Bilateral Viterbi Matching for 3D Rib Centerline Tracing in CT

arXiv:2610.16047v1 Announce Type: cross Abstract: Automatic extraction and anatomical numbering (R01-R12, L01-L12) of all 24 rib centerlines in thoracic CT is essential for unfolded rib visualization,

Hybrid Parallel Bessel KAN Model: a Kolmogorov Arnold Network: integrated framework for developing a novel architecture to reconstruct the fused-basis approach via a parameter free quadratic interaction

arXiv:2610.17779v1 Announce Type: new Abstract: The Kolmogorov-Arnold Network (KAN) challenges traditional MLPs by placing learnable activation functions on network edges. However, scaling KANs to spa

HYDRA: Representation Harmonized Tokenization for Multimodal Generation and Understanding

arXiv:2603.15228v3 Announce Type: replace Abstract: Unified Multimodal Models struggle to bridge the fundamental gap between the abstract representations needed for visual understanding and the detail

I built a cheap dual 3090 rig from used parts, but why isn't it much faster?

model-releasesr-localllama

Hey everyone, I recently put together a local LLM machine using mostly second hand hardware. I wanted to experiment with local models for app development without spending a fortune on a new workstatio

I built BitRun: A standalone runner for 1-bit LLMs (100–127 t/s on Apple Silicon & 40–45 t/s on PC CPUs with zero compile)

model-releasesr-localllama

I built BitRun because I wanted to run 1-bit ternary LLMs on ordinary laptops without melting my battery, spinning up a dedicated GPU, or wrestling with complex build environments. Right now, BitRun g

I2O2I-Nav: A Benchmark with a Modular Agent for Long-Horizon Indoor-to-Outdoor-to-Indoor Navigation

arXiv:2610.18307v1 Announce Type: new Abstract: Service and delivery robots often need to complete long-horizon navigation missions spanning indoor and outdoor environments. Existing embodied navigati

Image Tokenizers Should Be Trained Between Images

arXiv:2610.16759v1 Announce Type: new Abstract: Latent diffusion models generate images as codes of an image tokenizer, whose decoder turns them into the pixel image. Recent tokenizers improve how wel

In-context classification: Calibration and noise in linear attention with softmax readout

arXiv:2610.17061v1 Announce Type: cross Abstract: We study in-context binary classification in a simple attention model trained to minimise a logistic loss. Each prompt has a latent logistic teacher,

InCLAD: A Continual Learning Benchmark for Industrial Visual Anomaly Detection

arXiv:2610.15032v1 Announce Type: new Abstract: Industrial anomaly detection benchmarks have advanced rapidly, yet they remain largely static and therefore underrepresent deployment settings in which

IND-Eval: Aligning Evaluation and Simulation for Industrial Time Series Foundation Models

arXiv:2610.16652v1 Announce Type: new Abstract: We introduce IND-Eval, a public benchmark that organizes industrial time series across domains into source-specific forecasting tasks. Relative to estab

Information-Theoretic Foundations of Online Temperature Sampling

arXiv:2610.15043v1 Announce Type: new Abstract: Repetitive, degenerate generation is a persistent failure of LLM decoding, and the standard remedies (temperature, nucleus, and top-k sampling) are stat

InfoVis: Unified Slide Image Generation and Editing

arXiv:2610.16784v1 Announce Type: new Abstract: Generating and editing presentation slides requires models to combine accurate text rendering, instruction following, visual grounding, aesthetic design

InfraWorld: Motion-Aware World Modeling for Roadside 4D Occupancy Forecasting

arXiv:2610.14544v1 Announce Type: new Abstract: Roadside 4D occupancy forecasting predicts future semantic occupancy in a fixed infrastructure coordinate system. Roadside scenes are globally structure

inLoRA-MINT: Internal Representations for Auditing Training Data in Domain-adapted LLMs

arXiv:2610.18051v1 Announce Type: new Abstract: This work investigates the application of the Membership Inference Test (MINT) to large language models (LLMs) fine-tuned with LoRA, aiming to determine

Interactive 4D Volumetric Liquid Forecasting under Moving-Solid Interaction

arXiv:2610.16167v1 Announce Type: cross Abstract: We propose the task of Interactive 4D Volumetric Liquid Forecasting: predicting the spatiotemporal evolution of a future dense 3D liquid velocity fiel

Interactive Navigation Beyond Reachability: Benchmark and Agentic Framework

arXiv:2610.17089v1 Announce Type: new Abstract: Existing embodied navigation tasks commonly assume that traversability and object states remain fixed during an episode. Yet reaching a goal may require