Knowledge catalogue
arXiv:2604.21214v1 Announce Type: cross Abstract: Text-to-SQL models have significantly improved with the adoption of Large Language Models (LLMs), leading to their increasing use in real-world applic
arXiv:2603.21697v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) extend text-only LLMs with visual reasoning, but also introduce new safety failure modes under visual
arXiv:2604.21032v1 Announce Type: new Abstract: Multi-spectral imagery is a valuable input signal for Remote Sensing applications, such as land-use and land-cover classification and environmental moni
1. We believe in iterative deployment; although GPT-5.5 is already a smart model, we expect rapid improvements. Iterative deployment is a big part of our safety strategy; we believe the world will be
This Reddit post from r/ollama asks about story-writing language models that can run on a 5080 GPU with 16GB of VRAM . The discussion likely covers recommended open-source or quantized models suitable
arXiv:2604.19839v1 Announce Type: cross Abstract: Vision-language models (VLMs) have shown strong perception and reasoning abilities for instruction-following embodied agents. However, despite these a
arXiv:2411.00585v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have become foundational in modern language-driven software applications, profoundly influencing daily life. A cr
arXiv:2604.20707v1 Announce Type: new Abstract: Digital twins of natural systems must remain aligned with physical systems that evolve over time, are only partially observed, and are typically modeled
arXiv:2604.19786v1 Announce Type: new Abstract: Evaluating humor in large language models (LLMs) is an open challenge because existing approaches yield isolated, incomparable metrics rather than unifi
arXiv:2604.20677v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in socially sensitive settings, raising concerns about fairness and biases, particularly across i
arXiv:2510.26285v2 Announce Type: replace-cross Abstract: Prior work has shown that large language models (LLMs) often converge to accurate input embedding for numbers, based on sinusoidal representat
arXiv:2604.20079v1 Announce Type: cross Abstract: Auto-regressive Large Language Models (LLMs) achieve strong performance on coding tasks, but incur high memory and inference costs. Diffusion-based la
arXiv:2604.20296v1 Announce Type: cross Abstract: Survival analysis is a widely used statistical framework for modeling time-to-event data under censoring. Classical methods, such as the Cox proportio
arXiv:2510.14274v2 Announce Type: replace Abstract: Training effective multilingual embedding models presents unique challenges due to the diversity of languages and task objectives. Although small mu
arXiv:2509.15174v3 Announce Type: replace-cross Abstract: WARNING: This paper contains examples of offensive materials. To address the proliferation of toxic content on social media, we introduce SMAR
Things have been degrading super fast in Claude Code. I still use Claude Code, but my default is now Codex. I still prefer Opus models for coding, and so I will try again with the fixes. I appreciate
arXiv:2604.20289v1 Announce Type: new Abstract: Real-time world simulation is becoming a key infrastructure for scalable evaluation and online reinforcement learning of autonomous driving systems. Rec
Anthropic PBC is investigating a report that unauthorized users accessed Claude Mythos, the next-level artificial intelligence model the company says is powerful enough to enable dangerous cyberattack
arXiv:2510.17414v2 Announce Type: replace Abstract: Accurate prediction of lithium-ion battery capacity and its associated uncertainty is essential for reliable battery management but remains challeng
arXiv:2604.19125v1 Announce Type: new Abstract: Large language models have been extensively studied for emotion recognition and moral reasoning as distinct capabilities, yet the extent to which emotio
arXiv:2604.18973v1 Announce Type: cross Abstract: Air pollution is a worldwide public health threat that can cause or exacerbate many illnesses, including respiratory disease, cardiovascular disease,
arXiv:2603.20092v3 Announce Type: replace Abstract: Diffusion models generate structure by progressively transforming noise into data, yet the mechanisms underlying this transition remain poorly under
arXiv:2601.22737v2 Announce Type: replace Abstract: The robust safety of Vision-Language Large Models (VLLMs) against joint multilingual and multimodal threats remains severely underexplored. Current
arXiv:2604.16755v2 Announce Type: replace Abstract: As large language models (LLMs) are increasingly integrated into daily life, in roles ranging from high-stakes decision support to companionship, un
ml-intern by @huggingface is wild 🔥 You drop a high-level prompt (“build the best scientific reasoning model” or “crush healthcare benchmarks”) and this open-source agent does the entire post-training
arXiv:2409.09451v5 Announce Type: replace Abstract: Foundation models pre-trained using self-supervised learning have shown powerful transfer learning capabilities on various downstream tasks, includi
arXiv:2604.18839v1 Announce Type: cross Abstract: Looped transformers scale computational depth without increasing parameter count by repeatedly applying a shared transformer block and can be used for
OpenAI is shutting down text-embedding-3-small?!? I strongly believe that if you shut down a closed-source embedding model that you should open-source. Imaging the trillions of tokens that will no lon
OpenAI just open sourced a new 1.5B (50m active) model on HuggingFace with Apache 2.0 license! It's not a new LLM, this one is called Privacy Filter, and it's a PII detection model (checking if text h
arXiv:2604.19684v1 Announce Type: new Abstract: Explainable artificial intelligence (XAI) has predominantly focused on generating model-centric explanations that approximate the behavior of black-box
arXiv:2604.19092v1 Announce Type: cross Abstract: Recent advances in large-scale video world models have enabled increasingly realistic future prediction, raising the prospect of leveraging imagined v
arXiv:2604.19638v1 Announce Type: new Abstract: Multimodal Large Language Models are increasingly adopted as autonomous agents in interactive environments, yet their ability to proactively address saf
arXiv:2604.18966v1 Announce Type: cross Abstract: While language models have been adapted for tabular data generation, two fundamental limitations remain: (1) static fine-tuning produces models that c
arXiv:2512.07761v3 Announce Type: replace Abstract: Large language models have seen widespread adoption, yet they remain vulnerable to multi-turn jailbreak attacks, threatening their safe deployment.
We've published new research on how we post-train models for accurate search-augmented answers. Our SFT + RL pipeline improves search, citation quality, instruction following, and efficiency. With Qwe
arXiv:2604.16663v1 Announce Type: new Abstract: Landslide detection from high resolution satellite imagery is a critical task for disaster response and risk assessment, yet the relative effectiveness
arXiv:2604.18570v1 Announce Type: cross Abstract: Modern medicine generates vast multimodal data across siloed systems, yet no existing model integrates the full breadth and temporal depth of the clin
arXiv:2604.17258v1 Announce Type: new Abstract: Deploying a humanoid robot to manipulate a new object has traditionally required one to two days of effort: data collection, manual annotation, 3D model
arXiv:2604.18487v1 Announce Type: new Abstract: The Adversarial Humanities Benchmark (AHB) evaluates whether model safety refusals survive a shift away from familiar harmful prompt forms. Starting fro
Moonshot's Kimi K2.6 represents a significant update to their open-source language model, positioning it to compete with Anthropic's Claude Opus 4.6 and potentially ahead of DeepSeek v4. The refresh a
arXiv:2604.18489v1 Announce Type: cross Abstract: Large Language Models (LLMs) show promise in lyric-to-melody generation, but models trained with Supervised Fine-Tuning (SFT) often produce musically
arXiv:2604.16675v1 Announce Type: new Abstract: Action recognition is a fundamental ability for social species. Yet, its underlying computations are not well understood. Classical psychophysical studi
arXiv:2604.16851v1 Announce Type: cross Abstract: This dissertation explores how deep generative models can advance the analysis of challenging biological problems by integrating domain knowledge with
arXiv:2604.18187v1 Announce Type: cross Abstract: Large Audio-Language Models (LALMs) have made significant progress in audio understanding, yet they primarily operate as perception-and-answer systems
arXiv:2511.12642v2 Announce Type: replace-cross Abstract: Upgrades to current gravitational wave detectors for the next observation run and upcoming third-generation observatories, like the Einstein t
arXiv:2510.23807v5 Announce Type: replace-cross Abstract: Despite their successes in vision and language, foundation models have stumbled in pathology, revealing low accuracy, instability, and heavy c
arXiv:2509.20823v5 Announce Type: replace-cross Abstract: Time series captioning, the task of describing time series in natural language, requires numeric and temporal reasoning, trend interpretation,
Jody Godoy / Reuters: Clarifai says it has deleted 3M OkCupid user photos and facial-recognition models trained on them after the US FTC settled with OkCupid over privacy violations — Artificial intel
arXiv:2604.17961v1 Announce Type: new Abstract: In this work, we introduce DifFoundMAD, a parameter-efficient D-MAD framework that exploits the generalisation capabilities of vision foundation models
arXiv:2604.18277v1 Announce Type: new Abstract: Accurate dynamical modeling is essential for simulation and control of embodied systems, yet first-principles models of electromechanical systems often
arXiv:2603.11024v2 Announce Type: replace Abstract: VLMs have become increasingly proficient at a range of computer vision tasks, such as visual question answering and object detection. This includes
arXiv:2602.10764v2 Announce Type: replace Abstract: The slow iterative sampling nature remains a major bottleneck for the practical deployment of diffusion and flow-based generative models. While cons
arXiv:2604.17051v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated excellent performance in general language understanding, generation and other tasks. However, when fine-t
arXiv:2604.18167v1 Announce Type: new Abstract: Modern text-to-image (T2I) models amplify harmful societal biases, challenging their ethical deployment. We introduce an inference-time method that reli
arXiv:2412.02904v2 Announce Type: replace Abstract: Large language models (LLMs) have revolutionized the field of natural language processing with their impressive reasoning and question-answering cap
arXiv:2604.18260v1 Announce Type: new Abstract: Multimodal large language models have demonstrated remarkable capabilities in 2D vision, motivating their extension to 3D scene understanding. Recent st
arXiv:2510.02370v3 Announce Type: replace Abstract: Large language models leverage both parametric knowledge acquired during pretraining and in-context knowledge provided at inference time. Crucially,
arXiv:2604.16592v1 Announce Type: cross Abstract: This comprehensive report distinguishes prior works by the cognitive functions they innovate. Many works claim an almost 'human-like' cognitive capabi
I came up with a somewhat foolish new benchmark for testing image generation models, to exercise the new ChatGPT Images 2.0: 'Do a where's Waldo style image but it's where is the raccoon holding a ham
I find that open weights models over-perform on benchmarks compared to actual real-world usage, and Kimi feels like no exception. For example, a small amount of use will show that Kimi is not as good