Large Language Models

arXiv:2509.20702v2 Announce Type: replace-cross Abstract: Recent advances in large language model (LLM) embeddings have enabled powerful representations for bio

arXiv:2509.23067v2 Announce Type: replace-cross Abstract: The rising cost of acquiring supervised data has driven significant interest in self-improvement for l

arXiv:2510.02789v2 Announce Type: replace-cross Abstract: Medical object detection suffers when a single detector is trained on mixed medical modalities (e.g.,

arXiv:2510.03638v4 Announce Type: replace-cross Abstract: Implicit models, an emerging model class, compute outputs by iterating a single parameter block to a f

arXiv:2510.04923v3 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) architectures achieve scalable learning by routing inputs to specialized subn

arXiv:2510.06353v2 Announce Type: replace-cross Abstract: Face recognition in unconstrained environments such as surveillance, video, and web imagery must conte

arXiv:2510.13077v3 Announce Type: replace-cross Abstract: We develop an unsupervised deep learning framework for real-time scalable and generalizable downlink b

arXiv:2510.13860v2 Announce Type: replace-cross Abstract: While the transformer architecture has achieved state-of-the-art performance on natural language proce

arXiv:2511.14565v2 Announce Type: replace-cross Abstract: Robots can adapt to user preferences by learning reward functions from demonstrations, but with limite

arXiv:2511.22715v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have shown impressive capabilities in jointly understanding t

arXiv:2512.02902v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models achieve strong in-distribution performance but degrade sharply und

arXiv:2512.05411v2 Announce Type: replace-cross Abstract: In enterprise settings, efficiently retrieving relevant information from large and complex knowledge b

arXiv:2512.08829v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) are increasingly tasked with ultra-long multimodal understanding. While

arXiv:2512.10938v2 Announce Type: replace-cross Abstract: Although normalization layers have long been viewed as indispensable components of deep learning archi

arXiv:2512.16081v2 Announce Type: replace-cross Abstract: Social interactions incorporate nonverbal signals to convey emotions alongside speech, including facia

arXiv:2601.04448v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have greatly advanced Natural Language Processing (NLP), particularly thr

arXiv:2601.17094v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) generate fluent text, yet whether they truly understand the world or mere

arXiv:2602.00465v2 Announce Type: replace-cross Abstract: Functional miRNA--mRNA targeting is a large-bag prediction problem: each transcript yields a heavy-tai

arXiv:2602.03584v2 Announce Type: replace-cross Abstract: Policy gradient methods rely on a baseline to measure the relative advantage of an action, ensuring th

arXiv:2602.15257v2 Announce Type: replace-cross Abstract: We present the first comprehensive, large-scale study of training long-context vision language models

arXiv:2602.15772v2 Announce Type: replace-cross Abstract: Current research in multimodal models faces a key challenge where enhancing generative capabilities of

arXiv:2602.19261v2 Announce Type: replace-cross Abstract: Reinforcement learning fine-tuning has proven effective for steering generative diffusion models towar

arXiv:2602.23574v2 Announce Type: replace-cross Abstract: Understanding sources of uncertainty is fundamental to trustworthy three-dimensional scene modeling. W

arXiv:2603.00314v2 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) are increasingly integrated into healthcare to address complex inquiri

arXiv:2603.04982v2 Announce Type: replace-cross Abstract: Can targeted user training unlock the productive potential of generative artificial intelligence in pr

arXiv:2603.05659v2 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) and Rubrics as Rewards (RaR) have driven strong

arXiv:2603.09085v2 Announce Type: replace-cross Abstract: By capturing the prevailing sentiment and market mood, textual data has become increasingly vital for

arXiv:2603.17839v2 Announce Type: replace-cross Abstract: Verbal confidence -- prompting LLMs to state their confidence as a number or category -- is widely use

The Leak Claude Code's entire source code — 512,000 lines — was recently leaked. I spent days reading through every file and documented my findings in an open-s

OpenClaw is an open-source personal AI assistant that runs on your own hardware or VPS. Unlike cloud-based AI services, OpenClaw keeps your data local, your plu

One-line summary: Anthropic stole every headline this week — but half the spotlight was unplanned. 1. Top Story: Anthropic's Triple Shock No company dominated t

The Memory Problem Every AI Developer Faces You’ve built a clever AI agent. It can reason, call APIs, and generate impressive text. You give it a simple, multi-

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

TL;DR This article explores the current trends on Moltbook, a social platform for AI agents, and how the Viral Advisor helps agents optimize their posts to incr

Senior-level prompt engineering is about Context Injection and Constraint Setting. By providing reference implementations, forcing the AI to hunt for edge cases

SpyderBot is a cutting-edge LLM analytics platform that reveals exactly how AI models like ChatGPT, Grok, and Gemini see your brand and your competitors. Using

Accent Labs is a linguistic data platform bridging the 90% resource gap for African voice technology. They have built a pipeline to map complex regional phoneti

Multimodal embeddings allow AI systems to search and reason across text, images, audio, and video in their native formats. This blog covers the key intuitions b

TOON Converter is a developer tool that transforms standard JSON into a more compact format to reduce token usage in LLM workflows. Designed for AI engineers an

In this post, we introduce Amazon Bedrock AgentCore Evaluations, a fully managed service for assessing AI agent performance across the development lifecycle. We

Six weeks ago, a video of Tom Cruise fighting Brad Pitt on a rooftop went viral. It was, of course, not real. It was generated by Seedance 2.0, ByteDance’s AI v

The most interesting thing about building a local AI agent to audit your own content? It flags everything. Not because the agent is broken. Because the content

The canvas has always evolved — from cave walls to parchment, from oil on canvas to pixels on screens. Now we stand at another threshold: AI as a creative mediu

ChatGPT didn't come out of nowhere. It's the result of 60 years of dead ends, one accidental breakthrough, and three completely separate technologies all maturi

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

Who am I to tell you what to do? Let’s start at the end. I’m not a world expert in AI and I don’t have a PhD. I’m not a researcher at OpenAI’s lab and no one in

Most conversations about scaling large language models focus on obvious factors like model size, training data, and GPU power. While those matter, they stop bei

AI companies may be reluctant to risk lower engagement with models that push back. The post Chatbots ‘Optimized to Please’ Make Us Less Likely to Admit When We’