Large Language Models

arXiv:2512.12812v2 Announce Type: replace-cross Abstract: Prompt engineering has emerged as a critical factor influencing large language model (LLM) performance

arXiv:2512.21326v2 Announce Type: replace-cross Abstract: Separating signal from noise is central to experiments. Applying well-established statistical methods

arXiv:2601.01627v2 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) are increasingly deployed in healthcare field, it becomes essential to

arXiv:2601.06932v4 Announce Type: replace-cross Abstract: Matching place names across writing systems is a persistent obstacle to the integration of multilingua

arXiv:2601.10079v2 Announce Type: replace-cross Abstract: Reinforcement Learning (RL) has become essential for eliciting complex reasoning capabilities in Large

arXiv:2601.18987v4 Announce Type: replace-cross Abstract: Determining whether a program terminates is a central problem in computer science. Turing's foundation

arXiv:2601.22452v2 Announce Type: replace-cross Abstract: As AI chatbots shift from tools to companions, critical questions arise: who controls the conversation

arXiv:2602.00059v2 Announce Type: replace-cross Abstract: Iterative code generation with Large Language Models (LLMs) can be viewed as an optimization process g

arXiv:2602.00665v2 Announce Type: replace-cross Abstract: Customer-service question answering (QA) systems increasingly rely on conversational language understa

arXiv:2602.05548v3 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR), particularly GRPO, has become the standard for

arXiv:2602.06098v2 Announce Type: replace-cross Abstract: Coding assistants are increasingly utilized in test-driven software development, yet the theoretical m

arXiv:2602.08482v2 Announce Type: replace-cross Abstract: Vessel trajectory data from the Automatic Identification System (AIS) is used widely in maritime analy

arXiv:2602.13191v2 Announce Type: replace-cross Abstract: Video Language Models (VideoLMs) enable AI systems to understand temporal dynamics in videos. To fit w

arXiv:2602.16898v4 Announce Type: replace-cross Abstract: Task planning for robotic manipulation with large language models (LLMs) is an emerging area. Prior ap

arXiv:2602.21655v2 Announce Type: replace-cross Abstract: Image captioning remains a fundamental task for vision language understanding, yet ground-truth superv

arXiv:2602.23153v2 Announce Type: replace-cross Abstract: Large Multimodal Models (LMMs) that process 3D data typically rely on heavy, pre-trained visual encode

arXiv:2603.01305v2 Announce Type: replace-cross Abstract: Large multimodal models (LMMs) exhibit strong task generalization capabilities, offering new opportuni

arXiv:2603.01331v2 Announce Type: replace-cross Abstract: Discrete diffusion language models (dLLMs) generate text by iteratively denoising a masked sequence. H

arXiv:2603.01499v2 Announce Type: replace-cross Abstract: The rapid development of large language models (LLMs) has driven the widespread adoption of cloud-base

arXiv:2603.04427v4 Announce Type: replace-cross Abstract: Standard Transformer attention uses identical dimensionality for queries, keys, and values, yet these

arXiv:2603.07554v2 Announce Type: replace-cross Abstract: Nepal Bhasha (Newari), an endangered language of the Kathmandu Valley, remains digitally marginalized

arXiv:2603.08206v4 Announce Type: replace-cross Abstract: Tabular foundation models such as TabPFN and TabICL already produce full predictive distributions, yet

arXiv:2603.09964v2 Announce Type: replace-cross Abstract: As social virtual reality (VR) grows more popular, addressing accessibility for blind and low vision (

arXiv:2603.13793v2 Announce Type: replace-cross Abstract: Low resource languages present unique challenges for natural language processing due to the limited av

arXiv:2603.14354v2 Announce Type: replace-cross Abstract: End-to-End autonomous driving (E2E-AD) systems face challenges in lifelong learning, including catastr

arXiv:2603.16430v3 Announce Type: replace-cross Abstract: EngGPT2-16B-A3B is the latest iteration of Engineering Group's Italian LLM and it's built to be a Sove

arXiv:2603.16739v2 Announce Type: replace-cross Abstract: Decoding the orchestration of neural activity in electroencephalography (EEG) signals is a central cha

arXiv:2603.18532v2 Announce Type: replace-cross Abstract: The strong performance of large vision-language models (VLMs) trained with reinforcement learning (RL)

arXiv:2603.21879v2 Announce Type: replace-cross Abstract: Weather forecasting supports critical socioeconomic activities and complements environmental protectio

Key Takeaways Universal Claude.md can cut token use by up to 63%, which means you actually spend way less money using LLMs. Developers are fed up with prompt ha

Key Takeaways Devs have been quietly frustrated with Claude’s overly polite, wordy answers for a while. Trimming Claude’s output isn’t just about saving tokens,

Key Takeaways Devs are using Universal Claude.md to cut down Claude's wordiness and save on tokens, which means lower API bills. Cutting Claude’s longer answers

Key Takeaways An open-source tool called Claude.md just helped someone cut their AI token costs by 63%, which is wild. Most LLMs like Claude spit out a ton of u

The AI landscape is experiencing unprecedented growth and transformation. This post delves into the key developments shaping the future of artificial intelligen

Six weeks ago I gave my AI assistant a memory . It worked. No more re-explaining the project every session. Bugs got fixed once and stayed fixed. Then it follow

Users are flocking to Duck.ai. Is it a reaction to increasing concerns about AI companies and privacy? Here's what you should know.

Crow-9B-HERETIC is a 9-billion-parameter language model built on the Qwen 3.5 architecture and distilled from Claude Opus 4.6. The model excels at reasoning tas

The benchmark itself isn't the solution. It's the beginning of a new research direction, one forced by reality rather than chosen by preference. Models that loo

AI systems don’t “understand” your company—they reconstruct it from public signals. When those signals are fragmented, outdated, or inconsistent, AI outputs bec

According to a Quinnipiac University poll, 15% of Americans say they'd be willing to have a job where their direct supervisor was an AI program that assigned ta

LiteLLM had obtained two security compliance certifications via Delve and fell victim to some horrific credential-stealing malware last week.

This article is divided into three parts; they are: • How Attention Works During Prefill • The Decode Phase of LLM Inference • KV Cache: How to Make Decode More

Another iPhone update has just reached its first developer beta. There was a chance it would include the first glimpse of the brand-new Siri, but so far there’s

The AI landscape is experiencing unprecedented growth and transformation. This post delves into the key developments shaping the future of artificial intelligen

You send your AI agent a message. The upstream model returns a 429 — rate limited, try again later. Your agent framework dutifully retries. And retries. And ret

4 core pillars to get cited within AI searches You must shift your strategy from traditional SEO to Generative Engine Optimization (GEO). AI engines do not read

We shipped the AI layer for Kobin today — an agency operating system that replaces Slack, Notion, HubSpot, Linear, and Buffer. This is the technical story of ho

The current wave of investment in artificial intelligence reflects one of the largest capital shifts in modern technology, yet questions around financial return