Search: “models”

Can AI-Generated Persuasion Be Detected? Persuaficial Benchmark and AI vs. Human Linguistic Differences

model-releasesarxiv-cs-cl

arXiv:2601.04925v2 Announce Type: replace Abstract: Large Language Models (LLMs) can generate highly persuasive text, raising concerns about their misuse for propaganda, manipulation, and other harmfu

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CoDA: Towards Effective Cross-domain Knowledge Transfer via CoT-guided Domain Adaptation

DGX agent

arXiv:2604.19488v1 Announce Type: new Abstract: Large language models (LLMs) have achieved substantial advances in logical reasoning, yet they continue to lag behind human-level performance. In-contex

applicationsarxiv-cs-ai

22 Apr 2026

CreatiParser: Generative Image Parsing of Raster Graphic Designs into Editable Layers

arXiv:2604.19632v1 Announce Type: new Abstract: Graphic design images consist of multiple editable layers, such as text, background, and decorative elements, while most generative models produce raste

safetyarxiv-cs-cv

Dual Triangle Attention: Effective Bidirectional Attention Without Positional Embeddings

arXiv:2604.18603v1 Announce Type: cross Abstract: Bidirectional transformers are the foundation of many sequence modeling tasks across natural, biological, and chemical language domains, but they are

safetyarxiv-cs-lg

DW-Bench: Benchmarking LLMs on Data Warehouse Graph Topology Reasoning

arXiv:2604.18964v1 Announce Type: new Abstract: This paper introduces DW-Bench, a new benchmark that evaluates large language models (LLMs) on graph-topology reasoning over data warehouse schemas, exp

EgoMotion: Hierarchical Reasoning and Diffusion for Egocentric Vision-Language Motion Generation

arXiv:2604.19105v1 Announce Type: new Abstract: Faithfully modeling human behavior in dynamic environments is a foundational challenge for embodied intelligence. While conditional motion synthesis has

researcharxiv-cs-cv

Enforcing Reciprocity in Operator Learning for Seismic Wave Propagation

arXiv:2602.11631v2 Announce Type: replace-cross Abstract: Accurate and efficient wavefield modeling underpins seismic structure and source studies. Traditional methods comply with physical laws but ar

researcharxiv-cs-lg

Enjoyed the read? If you have deep experience in ML frameworks (training or inference) and love working on problems like these, our team is …

Enjoyed the read? If you have deep experience in ML frameworks (training or inference) and love working on problems like these, our team is hiring! ML Systems Engineer, Frameworks & Tooling: https://j

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Applications

Exploring Language-Agnosticity in Function Vectors: A Case Study in Machine Translation

arXiv:2604.19678v1 Announce Type: new Abstract: Function vectors (FVs) are vector representations of tasks extracted from model activations during in-context learning. While prior work has shown that

applicationsarxiv-cs-cl

Fast and Robust Diffusion Posterior Sampling for MR Image Reconstruction Using the Preconditioned Unadjusted Langevin Algorithm

model-releasesarxiv-cs-cv

arXiv:2512.05791v2 Announce Type: replace-cross Abstract: Purpose: The Unadjusted Langevin Algorithm (ULA) in combination with diffusion models can generate high quality MRI reconstructions with uncer

Local Ai

Flux 2-Klein-9B NVFP4 works well on my RTX 3050, but it takes 55sec to generate 1024 resolution.

local-air-stablediffusion

Flux 2-Klein-9B NVFP4 is a quantized image generation model that runs on mid-range GPUs like the RTX 3050. On this hardware, the model produces 1024-resolution images but with relatively slow inferenc

Tutorials

FoNE: Precise Single-Token Number Embeddings via Fourier Features

arXiv:2502.09741v2 Announce Type: replace Abstract: Large Language Models (LLMs) typically represent numbers using multiple tokens, which requires the model to aggregate these tokens to interpret nume

tutorialsarxiv-cs-cl

From Natural Language to Executable Narsese: A Neuro-Symbolic Benchmark and Pipeline for Reasoning with NARS

arXiv:2604.18873v1 Announce Type: new Abstract: Large language models (LLMs) are highly capable at language generation, but they remain unreliable when reasoning requires explicit symbolic structure,

Agents

Google unveils two new TPUs designed for the 'agentic era'

Google unveiled two eighth-generation Tensor Processing Units—the TPU 8t for training and TPU 8i for inference—designed with specialized architectures for AI model training and agent development. The

agentsars-technica

Has Automated Essay Scoring Reached Sufficient Accuracy? Deriving Achievable QWK Ceilings from Classical Test Theory

arXiv:2604.19131v1 Announce Type: new Abstract: Automated essay scoring (AES) is commonly evaluated on public benchmarks using quadratic weighted kappa (QWK). However, because benchmark labels are ass

Tools

https://x.com/tanayj/status/2046733145446502805?s=46

https://x.com/tanayj/status/2046733145446502805?s=46 My read on the structure of this deal: 1. xAI is leveraging Cursor's data / traces to help train a better coding model (both Grok base model and po

toolsswyx--x

KG-ViP: Bridging Knowledge Grounding and Visual Perception in Multi-modal LLMs for Visual Question Answering

arXiv:2601.11632v2 Announce Type: replace Abstract: Multi-modal Large Language Models (MLLMs) for Visual Question Answering (VQA) often suffer from dual limitations: knowledge hallucination and insuff

researcharxiv-cs-cv

Knowledge-Guided Time-Varying Causal Inference for Arctic Sea Ice Dynamics

arXiv:2601.17647v2 Announce Type: replace-cross Abstract: Quantifying the causal relationship between sea ice thickness and sea surface height (SSH) is essential for understanding the mechanisms drivi

safetyarxiv-cs-ai

Tutorials

Latent Linear Quadratic Regulator for Robotic Control Tasks

arXiv:2407.11107v3 Announce Type: replace-cross Abstract: Model predictive control (MPC) has played a more crucial role in various robotic control tasks, but its high computational requirements are co

tutorialsarxiv-cs-lg

Making ChatGPT better for clinicians

OpenAI describes improvements and adaptations made to ChatGPT to better serve clinical and healthcare professionals. The work likely addresses how the model can be made more reliable, accurate, and us

model-releasesopenai

Maximizing Gemini: Google Cloud makes its bid to build the operating system for enterprise AI

model-releasessiliconangle

Google LLC has emerged as the only cloud “hyperscaler” with a leading frontier artificial intelligence large language model – Gemini – and today it issued a raft of announcements designed to capitaliz

ODMA: On-Demand Memory Allocation Strategy for LLM Serving on LPDDR-Class Accelerators

arXiv:2512.09427v5 Announce Type: replace-cross Abstract: Existing memory management techniques severely hinder efficient Large Language Model serving on accelerators constrained by poor random-access

Applications

Prompt to Pwn: Automated Exploit Generation for Smart Contracts

arXiv:2508.01371v3 Announce Type: replace-cross Abstract: Smart contracts are important for digital finance, yet they are hard to patch once deployed. Prior work has mainly explored LLMs for smart con

applicationsarxiv-cs-ai

Qwen3.6 27B is now in LM Studio! Vision, reasoning, and agentic tool calling - running locally on your computer. Surpasses previous Qwen mod…

model-releaseslm-studio--x

Qwen3.6 27B is now in LM Studio! Vision, reasoning, and agentic tool calling - running locally on your computer. Surpasses previous Qwen models many times its size 🚀👾🔥 https://lmstudio.ai/models/qwen/

Industry

Qwen3.6-27B-TQ3_4S is insanely good! https://huggingface.co/YTan2000/Qwen3.6-27B-TQ3_4S fit on my 16GB with 32k context Two prompts and I ge…

Qwen3.6-27B-TQ3_4S is a quantized 27 billion parameter language model that fits on 16GB of VRAM while supporting a 32k token context window, demonstrating strong performance across tested prompts. The

industryclem-delangue--x

ReefNet: A Large-Scale Dataset and Benchmark for Fine-Grained Coral Reef Recognition

arXiv:2510.16822v3 Announce Type: replace-cross Abstract: Coral reefs are rapidly declining under anthropogenic pressures (e.g., climate change), creating an urgent need for scalable and automated mon

Applications

Seeing Candidates at Scale: Multimodal LLMs for Visual Political Communication on Instagram

arXiv:2604.19489v1 Announce Type: new Abstract: This paper presents a computational case study that evaluates the capabilities of specialized machine learning models and emerging multimodal large lang

applicationsarxiv-cs-cv

ShadowPEFT: Shadow Network for Parameter-Efficient Fine-Tuning

arXiv:2604.19254v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning (PEFT) reduces the training cost of full-parameter fine-tuning for large language models (LLMs) by training only a sma

SpecAgent: A Speculative Retrieval and Forecasting Agent for Code Completion

arXiv:2510.17925v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) excel at code-related tasks but often struggle in realistic software repositories, where project-specific APIs an

Agents

Step 3.5 Flash is now live for Nous Portal users, free for the next 10 days. If you're running Hermes Agent with Nous Portal as your provide…

Step 3.5 Flash is now live for Nous Portal users, free for the next 10 days. If you're running Hermes Agent with Nous Portal as your provider, run 'hermes update' and then 'hermes model' to configure

agentsnous-research--x

StochasTok: Improving Fine-Grained Subword Understanding in LLMs

arXiv:2506.01687v3 Announce Type: replace Abstract: Subword-level understanding is integral to numerous tasks, including understanding multi-digit numbers, spelling mistakes, abbreviations, rhyming, a

researcharxiv-cs-cl

Structure-Semantic Decoupled Modulation of Global Geospatial Embeddings for High-Resolution Remote Sensing Mapping

arXiv:2604.19591v1 Announce Type: new Abstract: Fine-grained high-resolution remote sensing mapping typically relies on localized visual features, which restricts cross-domain generalizability and oft

researcharxiv-cs-cv

Symbolic Quantile Regression for the Interpretable Prediction of Conditional Quantiles

arXiv:2508.08080v2 Announce Type: replace Abstract: Symbolic Regression (SR) is a well-established framework for generating interpretable or white-box predictive models. Although SR has been successfu

safetyarxiv-cs-lg

Time Series Augmented Generation for Financial Applications

arXiv:2604.19633v1 Announce Type: new Abstract: Evaluating the reasoning capabilities of Large Language Models (LLMs) for complex, quantitative financial tasks is a critical and unsolved challenge. St

TRN-R1-Zero: Text-rich Network Reasoning via LLMs with Reinforcement Learning Only

arXiv:2604.19070v1 Announce Type: new Abstract: Zero-shot reasoning on text-rich networks (TRNs) remains a challenging frontier, as models must integrate textual semantics with relational structure wi

safetyarxiv-cs-cl

Tools

Try Kimi K2.6 now on the AI Native Cloud: http://www.together.ai/models/kimi-k26#

Kimi K2.6 is now available for use on Together AI's cloud platform, which offers AI model deployment and inference services. This announcement indicates the model has been added to Together AI's roste

toolstogether-ai--x

Tstars-Tryon 1.0: Robust and Realistic Virtual Try-On for Diverse Fashion Items

model-releasesarxiv-cs-cv

arXiv:2604.19748v1 Announce Type: new Abstract: Recent advances in image generation and editing have opened new opportunities for virtual try-on. However, existing methods still struggle to meet compl

Two-dimensional early exit optimisation of LLM inference

arXiv:2604.18592v1 Announce Type: cross Abstract: We introduce a two-dimensional (2D) early exit strategy that coordinates layer-wise and sentence-wise exiting for classification tasks in large langua

Local Ai

What Makes an LLM a Good Optimizer? A Trajectory Analysis of LLM-Guided Evolutionary Search

arXiv:2604.19440v1 Announce Type: new Abstract: Recent work has demonstrated the promise of orchestrating large language models (LLMs) within evolutionary and agentic optimization systems. However, th

local-aiarxiv-cs-cl

What’s new with compute: Scaling core and agentic workloads

model-releasesgoogle-cloud-ai

At Google Cloud Next, we’re announcing a range of compute capabilities to enable your core general purpose and AI workloads for the agentic world with higher performance and lower costs. Why it matter

When Does Verification Pay Off? A Closer Look at LLMs as Solution Verifiers

arXiv:2512.02304v2 Announce Type: replace Abstract: Large language models (LLMs) can act as both problem solvers and solution verifiers, where the latter select high-quality answers from a pool of sol

researcharxiv-cs-cl

Adaptive Text Anonymization: Learning Privacy-Utility Trade-offs via Prompt Optimization

model-releasesarxiv-cs-cl

arXiv:2602.20743v2 Announce Type: replace Abstract: Anonymizing textual documents is a highly context-sensitive problem: the appropriate balance between privacy protection and utility preservation var

Agents

Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligence

arXiv:2604.18292v1 Announce Type: cross Abstract: Large language models are increasingly expected to serve as general-purpose agents that interact with external, stateful tool environments. The Model

agentsarxiv-cs-cl

Agentic Risk-Aware Set-Based Engineering Design

model-releasesarxiv-cs-lg

arXiv:2604.16687v1 Announce Type: cross Abstract: This paper introduces a multi-agent framework guided by Large Language Models (LLMs) to assist in the early stages of engineering design, a phase ofte

An Integrated Deep-Learning Framework for Peptide-Protein Interaction Prediction and Target-Conditioned Peptide Generation with ConGA-PePPI and TC-PepGen

model-releasesarxiv-cs-lg

arXiv:2604.18467v1 Announce Type: new Abstract: Motivation: Peptide-protein interactions (PepPIs) are central to cellular regulation and peptide therapeutics, but experimental characterization remains

An `Inverse' Experimental Framework to Estimate Market Efficiency

arXiv:2604.18130v1 Announce Type: new Abstract: Digital marketplaces processing billions of dollars annually represent critical infrastructure in sociotechnical ecosystems, yet their performance optim

safetyarxiv-cs-lg

An Uncertainty-Aware Loss Function Incorporating Fuzzy Logic: Application to MRI Brain Image Segmentation

model-releasesarxiv-cs-cv

arXiv:2604.16490v1 Announce Type: new Abstract: Accurate brain image segmentation, particularly for distinguishing various tissues from magnetic resonance imaging (MRI) images, plays a pivotal role in

Anthropic gets $5B investment from Amazon, will use it to buy Amazon chips

model-releasesars-technica

Amazon announced a 5 billion investment in Anthropic, with up to 20 billion more tied to commercial milestones. Anthropic committed to spending over $100 billion on AWS technologies over the next deca