Search: “models”

Tools as Continuous Flow for Evolving Agentic Reasoning

arXiv:2605.07339v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in orchestrating tools for reasoning tasks. However, existing methods rely on a s

11 May 2026

TraceAV-Bench: Benchmarking Multi-Hop Trajectory Reasoning over Long Audio-Visual Videos

DGX agent

arXiv:2605.07593v1 Announce Type: new Abstract: Real-world audio-visual understanding requires chaining evidence that is sparse, temporally dispersed, and split across the visual and auditory streams,

model-releasesarxiv-cs-cv

11 May 2026

Tutorials

Transfer Learning Across Fast- and Full-Simulation Domains in High-Energy Physics

arXiv:2605.07471v1 Announce Type: new Abstract: Machine-learning models in high-energy physics are often trained on simulated data, where fully simulated samples are computationally expensive while fa

tutorialsarxiv-cs-lg

11 May 2026

Industry

We’re dropping two open source SLMs this week. 1. One of them matches SOTA accuracy at up to 93x smaller. 2. The other one beats a recent Op…

Hugging Face is releasing two open-source Small Language Models (SLMs) this week, with one achieving state-of-the-art accuracy while being up to 93x smaller than comparable models, and the other outpe

industryclem-delangue--x

11 May 2026

Open sourced an iOS app that runs LLMs on-device with llama.cpp, and lets you plug in your own Ollama for automatic health insights from HealthKit

An iOS application that enables large language models to run directly on-device using llama.cpp technology, allowing users to integrate their own Ollama instances for processing Apple HealthKit data t

model-releasesr-ollama

9 May 2026

Industry

llamacpp is gonna get MTP support soon! 🚀

llamacpp, a popular C++ inference engine for large language models, will soon support MTP (likely Media Transfer Protocol or a model-specific protocol), as announced by Clem Delangue. This addition wi

industryclem-delangue--x

8 May 2026

OpenAI introduces GPT‑5.5‑Cyber for high-impact cybersecurity research

model-releasessiliconangle

OpenAI Group PBC has developed a version of GPT-5.5 that is specifically optimized for cybersecurity research. GPT‑5.5‑Cyber, as the model is called, made its debut on Thursday. It’s available in limi

8 May 2026

We're co-hosting a couple of hackathons in San Francisco next week. Come build with Claude 👇

model-releasesboris-cherny--x

Anthropic is hosting hackathons in San Francisco where developers can build projects using Claude, Anthropic's AI model. The announcement invites the developer community to participate in these upcomi

8 May 2026

A Comparative Study of PyCaret AutoML and CNN-BiLSTM for Binary Hate Speech Detection in Indonesian Twitter

arXiv:2605.04885v1 Announce Type: new Abstract: This paper compares a PyCaret AutoML branch and a CNN-BiLSTM branch for binary hate speech detection on Indonesian Twitter using the HS label from the c

Agent harnesses have an expiration date

A benchmark-driven look at why agent harnesses need adaptive finish logic as model behavior changes across Claude, GPT-4o, and Gemma. The post Agent harnesses have an expiration date appeared first on

model-releasesarize-ai

Agents

ARIS: Autonomous Research via Adversarial Multi-Agent Collaboration

arXiv:2605.03042v1 Announce Type: cross Abstract: This report describes ARIS (Auto-Research-in-sleep), an open-source research harness for autonomous research, including its architecture, assurance me

agentsarxiv-cs-ai

Assessing Cognitive Effort in L2 Idiomatic Processing: An Eye-Tracking Dataset

arXiv:2605.04857v1 Announce Type: new Abstract: This paper presents the development and validation of an eye-tracking dataset designed to investigate how second-language (L2) learners process idiomati

AsymmetryZero: A Framework for Operationalizing Human Expert Preferences as Semantic Evals

arXiv:2605.04083v1 Announce Type: new Abstract: Much of the focus in RL today is on evaluation design: building meaningful evals that serve simultaneously as benchmarks and as well-defined reward sign

BenCSSmark: Making the Social Sciences Count in LLM Research

arXiv:2605.04886v1 Announce Type: new Abstract: This position paper argues that the under-representation of social science tasks in contemporary LLM benchmarks limits advances in both LLM evaluation a

Research

Bilinear Mamba-Koopman Neural MPC for Varying Dynamics

arXiv:2605.04793v1 Announce Type: new Abstract: Koopman-based neural MPC models generate time-varying dynamics from historical data, but preserve convexity by enforcing that the system operator is ind

researcharxiv-cs-lg

Research

Consensus Entropy: Harnessing Multi-VLM Agreement for Self-Verifying and Self-Improving OCR

arXiv:2504.11101v4 Announce Type: replace Abstract: Optical Character Recognition (OCR) is fundamental to Vision-Language Models (VLMs) and high-quality data generation for LLM training. Yet, despite

researcharxiv-cs-cv

ConsisVLA-4D: Advancing Spatiotemporal Consistency in Efficient 3D-Perception and 4D-Reasoning for Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2605.05126v1 Announce Type: new Abstract: Current Vision-Language-Action (VLA) models primarily focus on mapping 2D observations to actions, but exhibit notable limitations in spatiotemporal per

DALight-3D: A Lightweight 3D U-Net for Brain Tumor Segmentation from Multi-Modal MRI

arXiv:2605.04518v1 Announce Type: new Abstract: Automatic brain tumor segmentation from multi-modal MRI remains challenging because volumetric models often incur substantial computational cost. This p

Research

Dataset-Driven Channel Masks in Transformers for Multivariate Time Series

arXiv:2410.23222v3 Announce Type: replace Abstract: Recent advancements in foundation models have been successfully extended to the time series (TS) domain, facilitated by the emergence of large-scale

researcharxiv-cs-lg

Discovering New Theorems via LLMs with In-Context Proof Learning in Lean

arXiv:2509.14274v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated significant promise in formal theorem proving. In this study, we investigate the ability of LLMs to d

Safety

Elicitation Matters: How Prompts and Query Protocols Shape LLM Surrogates under Sparse Observations

arXiv:2605.04764v1 Announce Type: new Abstract: Large language models are increasingly used as surrogate models for low-data optimization, but their optimizer-facing prediction and its uncertainty rem

safetyarxiv-cs-cl

Applications

ELVIS: Ensemble-Calibrated Latent Imagination for Long-Horizon Visual MPC

arXiv:2605.04709v1 Announce Type: new Abstract: A central challenge of visual control with model-based reinforcement learning (RL) is reliable long-horizon planning: long rollouts with learned latent

applicationsarxiv-cs-lg

Empirical Study of Pop and Jazz Mix Ratios for Genre-Adaptive Chord Generation

arXiv:2605.04998v1 Announce Type: cross Abstract: Chord progression generation is practically important but understudied. Most large-scale symbolic music systems target melody, multi-track arrangement

Explaining and Preventing Alignment Collapse in Iterative RLHF

arXiv:2605.04266v1 Announce Type: new Abstract: Reinforcement learning from human feedback (RLHF) typically assumes a static or non-strategic reward model (RM). In iterative deployment, however, the p

Feature Identification via the Empirical NTK

arXiv:2510.00468v4 Announce Type: replace Abstract: We provide evidence that eigenanalysis of the empirical neural tangent kernel (eNTK) can surface feature directions in trained neural networks. Acro

Fragile Knowledge, Robust Instruction-Following: The Width Pruning Dichotomy in Llama-3.2

arXiv:2512.22671v2 Announce Type: replace Abstract: Structured width pruning of GLU-MLP layers, guided by the Maximum Absolute Weight (MAW) criterion, reveals a systematic dichotomy in how reducing th

Generalization Bounds of Spiking Neural Networks via Rademacher Complexity

arXiv:2605.02927v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) have garnered increasing attention as one of bio-inspired models due to their great potential in neuromorphic computing

Generative Quantum-inspired Kolmogorov-Arnold Eigensolver

arXiv:2605.04604v1 Announce Type: cross Abstract: High-performance computing (HPC) is increasingly important for scalable quantum chemistry workflows that couple classical generative models, quantum c

Intermediate Representations are Strong AI-Generated Image Detectors

arXiv:2605.04358v1 Announce Type: new Abstract: The rapid advancement in generative AI models has enabled the creation of photorealistic images. At the same time, there are growing concerns about the

Local Ai

LTX 2.3 Slow Motion

local-air-stablediffusion

LTX-2.3 is an open-source video generation model capable of producing slow-motion effects and hyper-detailed visuals , with 4K output up to 20 seconds and native audio . The model addresses creator pa

MP-ISMoE: Mixed-Precision Interactive Side Mixture-of-Experts for Efficient Transfer Learning

arXiv:2605.04058v1 Announce Type: new Abstract: Parameter-efficient transfer learning (PETL) has emerged as a pivotal paradigm for adapting pre-trained foundation models to downstream tasks, significa

Notes on the xAI/Anthropic data center deal

model-releasessimon-willison

There weren't a lot of big new announcements from Anthropic at yesterday's Code w/ Claude event, but the biggest by far was the deal they've struck with SpaceX/xAI to use 'all of the capacity of their

OpenVTON-Bench: A Large-Scale High-Resolution Benchmark for Controllable Virtual Try-On Evaluation

arXiv:2601.22725v3 Announce Type: replace Abstract: Recent advances in diffusion models have significantly elevated the visual fidelity of Virtual Try-On (VTON) systems, yet reliable evaluation remain

Safety

OracleProto: A Reproducible Framework for Benchmarking LLM Native Forecasting via Knowledge Cutoff and Temporal Masking

arXiv:2605.03762v1 Announce Type: new Abstract: Large language models are moving from static text generators toward real-world decision-support systems, where forecasting is a composite capability tha

safetyarxiv-cs-ai

Testing ads in ChatGPT

OpenAI announced a test of advertisements within ChatGPT, marking the company's exploration of ad-supported monetization models alongside its existing subscription offerings. The initiative aims to ba

model-releasesopenai

Transformation Categorization Based on Group Decomposition Theory Using Parameter Division

arXiv:2605.04056v1 Announce Type: new Abstract: Representation learning seeks meaningful sensory representations without supervision and can model aspects of human development. Although many neural ne

UFAL-CUNI at SemEval-2026 Task 11: An Efficient Modular Neuro-symbolic Method for Syllogistic Reasoning

arXiv:2605.04941v1 Announce Type: new Abstract: This paper describes our system submitted to SemEval-2026 Task 11: Disentangling Content and Formal Reasoning in Large Language Models. We present an ef

who’s adding this to reachy mini?

model-releasesclem-delangue--x

who’s adding this to reachy mini? Introducing GPT-Realtime-2 in the API: our most intelligent voice model yet, bringing GPT-5-class reasoning to voice agents. Voice agents are now real-time collaborat

AI and Open-data Driven Scalable Solar Power Profiling

arXiv:2605.02738v1 Announce Type: new Abstract: Solar photovoltaic (PV) deployment is expanding rapidly, yet detailed, up-to-date information on the spatial distribution and capacity of rooftop PV rem

Amortized Variational Inference for Joint Posterior and Predictive Distributions in Bayesian Uncertainty Quantification

arXiv:2605.03710v1 Announce Type: cross Abstract: Bayesian predictive inference propagates parameter uncertainty to quantities of interest through the posterior-predictive distribution. In practice, t

Artificial Jagged Intelligence as Uneven Optimization Energy Allocation Capability Concentration, Redistribution, and Optimization Governance

arXiv:2605.01420v1 Announce Type: new Abstract: Artificial Jagged Intelligence (AJI) denotes a recurring pattern in which large learning systems exhibit strong local capabilities while remaining weak

Benchmarking Document Parsers on Mathematical Formula Extraction from PDFs

arXiv:2512.09874v2 Announce Type: replace Abstract: Correctly parsing mathematical formulas from PDFs is critical for training large language models and building scientific knowledge bases from academ

Calibration of the underlying surface parameters for urban flood using latent variables and adjoint equation

arXiv:2605.02959v1 Announce Type: new Abstract: Calibrating the urban underlying surface parameters is crucial for urban flood simulation. We formulate the parameter calibration problem into an optimi

ContextCov: Deriving and Enforcing Executable Constraints from Agent Instruction Files

arXiv:2603.00822v2 Announce Type: replace-cross Abstract: As Large Language Model (LLM) agents increasingly execute complex, autonomous software engineering tasks, developers rely on natural language

DALPHIN: Benchmarking Digital Pathology AI Copilots Against Pathologists on an Open Multicentric Dataset

arXiv:2605.03544v1 Announce Type: new Abstract: Foundation models with visual question answering capabilities for digital pathology are emerging. Such unprecedented technology requires independent ben

DiagramNet: An End-to-End Recognition Framework and Dataset for Non-Standard System-Level Diagrams

arXiv:2605.01338v1 Announce Type: new Abstract: System-level diagrams encode the architectural blueprint of chip design, specifying module functions, dataflows, and interface protocols. However, non-s

DocSync: Agentic Documentation Maintenance via Critic-Guided Reflexion

arXiv:2605.02163v1 Announce Type: cross Abstract: Software documentation frequently drifts from executable logic as codebases evolve, creating technical debt that degrades maintainability and causes d

Effective Performance Measurement: Challenges and Opportunities in KPI Extraction from Earnings Calls

arXiv:2605.03147v1 Announce Type: new Abstract: Earnings calls are a key source of financial information about public companies. However, extracting information from these calls is difficult. Unlike t