Search: “models”

arXiv:2605.29379v1 Announce Type: new Abstract: We present BrahmicTokenizer-131K, a 131,072-vocabulary byte-level BPE tokenizer that closes the Brahmic compression gap at the 131K-vocabulary class whi

CineStill 800T Night Film LoRA is a machine learning model addon for Stable Diffusion that applies a cinematic night aesthetic to AI-generated images, using the trigger word 'c1n3st1ll' at strength 0.

arXiv:2605.30131v1 Announce Type: new Abstract: Radiology report generation (RRG) is commonly formulated as a single-path generation task, where a multimodal large language model (MLLM) produces one d

ChatGPT diagnosed 40 million people with a disease that was invented as a joke. Not a real disease. Not a misunderstood disease. A completely fictional condition with a fake name, fake papers, and fak

arXiv:2605.29935v1 Announce Type: cross Abstract: Autonomous driving systems are commonly trained and evaluated within limited geographic regions, which hinders their scalability when deployed in new

Claude really can roleplay an economist. I love this little comment Claude made after some robustness checks on the paper it wrote: 'On a 1–10 identification scale, I'd now put the paper at about 4.5

arXiv:2602.10637v2 Announce Type: replace Abstract: Sampling equilibrium molecular configurations from the Boltzmann distribution is a longstanding challenge. Boltzmann Generators (BGs) address this b

arXiv:2605.30332v1 Announce Type: new Abstract: Diffusion models achieve state-of-the-art image synthesis, with their generative trajectories fundamentally exhibiting a spectral bias, resolving low-fr

Command A+ sets a new high for Cohere's machine translation capabilities. Opening a clear gap over open source peers Mistral Medium 3.5, DeepSeek, & OpenAI's gpt-oss, as well as Claude Opus 4.6. A+ al

arXiv:2605.29268v1 Announce Type: cross Abstract: LLM-guided evolutionary search (Evolve systems) has reached state-of-the-art results on mathematical and combinatorial tasks, yet most existing system

arXiv:2605.29054v1 Announce Type: cross Abstract: Coding agents increasingly act as codebase-scale collaborators that can assist with codebase conversion, but this progress has exposed a critical weak

arXiv:2605.30000v1 Announce Type: new Abstract: Front-end web code has become a core product surface for every frontier LLM release, yet evaluating these interactive applications at development speed

arXiv:2605.30334v1 Announce Type: new Abstract: Large Language Models (LLMs) have revolutionized various fields, yet their training efficiency is heavily reliant on effective data curation. While data

arXiv:2605.30107v1 Announce Type: new Abstract: Creating spoken dialogue datasets is methodologically challenging, and these challenges are amplified when the goal is to build multilingual, multi-para

arXiv:2605.29042v1 Announce Type: new Abstract: Human coordination often relies on the ability to influence the beliefs of others through strategic action. In multi-agent reinforcement learning, oppon

arXiv:2605.30090v1 Announce Type: new Abstract: Long-form video generation is rapidly moving from short, single-scene synthesis toward minute-long, multi-shot creation with narrative structure, cinema

Document Parsing + Gemini 🔥 Excited to collaborate with the Google team on this, here's to many more! The team at @llama_index built an awesome template using LlamaParse and the new Managed Agents in

arXiv:2503.20897v2 Announce Type: replace Abstract: Semi-supervised domain generalization (SSDG) leverages a small fraction of labeled data alongside unlabeled data to enhance model generalization. Mo

This post likely describes a tool or system for planning autonomous drone flight paths, possibly involving visualization or interactive path-drawing interfaces. It may demonstrate how users can create

arXiv:2605.30010v1 Announce Type: new Abstract: Video large language models (Video-LLMs) have demonstrated strong capabilities in video understanding tasks. However, their practical deployment is stil

arXiv:2605.30337v1 Announce Type: new Abstract: Test-time finetuning (TTFT) is a rapidly evolving paradigm that adapts a language model to each prompt by retrieving related sequences, updating the mod

arXiv:2605.29630v1 Announce Type: cross Abstract: End-to-end agent-memory benchmarks report a single hit@k per retriever, confounding lexical leakage (uncontrolled query/gold/distractor entity overlap

arXiv:2605.29505v1 Announce Type: new Abstract: Online 3D scene perception in real time is essential for robotics, AR/VR, and autonomous systems, particularly in edge computing scenarios where computa

arXiv:2605.29002v1 Announce Type: new Abstract: Federated reinforcement learning enables decentralized agents to collaboratively improve policies or value estimates without exchanging raw trajectories

arXiv:2605.29460v1 Announce Type: new Abstract: Federated fine-tuning of foundation models with Low-Rank Adaptation (LoRA) provides an efficient solution for reducing communication and computation cos

arXiv:2605.29317v1 Announce Type: new Abstract: Parameter-efficient fine-tuning(PEFT) has largely focused on LoRA and its accuracy-oriented variants, leaving the original goal of reducing trainable pa

arXiv:2605.28826v1 Announce Type: new Abstract: In modern LLMs, linguistic features function not as stylistic artifacts but as probes of probability mass, allocated under training alignment objectives

arXiv:2605.30014v1 Announce Type: new Abstract: Urban trajectories play a crucial role in modeling urban dynamics and supporting various smart city applications. However, privacy concerns restrict acc

arXiv:2507.21429v3 Announce Type: replace-cross Abstract: We study local linear convergence of gradient descent for finite-width feedforward networks under the squared empirical loss. Prior work shows

arXiv:2605.29768v1 Announce Type: new Abstract: Existing traffic forecasting benchmarks assume a fixed sensor set, but real road-sensor networks grow continuously as the road network changes year by y

arXiv:2605.28965v1 Announce Type: new Abstract: Linking free-text phenotype descriptions to ontology terms, typically referred to as phenotype annotation, is essential for the cross-study integration

arXiv:2605.29494v1 Announce Type: new Abstract: Deep neural network training involves both forward propagation (from features through logits to loss) and backward propagation (from loss through gradie

Reece Rogers / Wired: Hands-on with Gemini Spark beta rolling out to AI Ultra subs: planned a birthday party from emails and calendar, but called a live-in boyfriend a “close friend” — Google's new AI

arXiv:2605.30058v1 Announce Type: new Abstract: While LLM agents have demonstrated remarkable task-oriented abilities such as planning, reasoning, and action, few works have treated them as complete h

Here's an extended edit of the quote that includes a following fragment where Andrew Macdonald called the trade 'harder to justify' - full, unedited transcript is here: https://gist.github.com/simonw/

arXiv:2605.29442v1 Announce Type: cross Abstract: AI coding agents increasingly act directly within software environments, yet existing analyses of their failures rely on benchmark trajectories that m

How lucky are you to have been born when and where you are? Had Opus 4.8 in Claude Code whip up a new visualization of all humans who ever lived. In addition to being neat, it is an interesting test o

I GOT THE DOMAIN! I FINALLY GOT IT!!!!!!!!!!1 🥳🎉 Paint​.NET is now at https://paint.net! Well, it will be just as soon as I push all the buttons to migrate content and set up redirects from getpaint​.

- I still get nonstop questions about use cases, even though I think thinking about things in the use case framework is the wrong way of thinking about it - Enterprises are starting to see actual busi

arXiv:2605.30179v1 Announce Type: cross Abstract: Parameter-efficient adaptation has made LLMs practical for domain prediction, but standard LoRA still relies on a static low-rank update and does not

Simon Willison expresses skepticism about reports claiming Uber overspent on AI and was disappointed with the results, indicating he investigated the story and found issues with its accuracy or framin

arXiv:2605.29776v1 Announce Type: new Abstract: Vision-Language Models (VLMs) such as CLIP demonstrate strong zero-shot generalization, but their performance significantly degrades in cross-domain sce

In conversation with OpenAI’s @markchen90, Terence reflects on a future where AI reduces the cognitive friction of research, helps preserve the paths behind discovery, and expands what mathematicians

arXiv:2605.29405v1 Announce Type: new Abstract: Decision-making from offline datasets typically warm-starts a policy or score model from fixed offline data and then refines it with limited online inte

arXiv:2605.29771v1 Announce Type: new Abstract: Intelligent wearable technology plays an increasingly important role in human-computer interaction, motion, and health monitoring. To ensure comfort and

arXiv:2605.29371v1 Announce Type: cross Abstract: We study the subclass of potential mean-field games in which the running interaction cost and the terminal target cost are both expressed through repr