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arXiv:2508.21589v1 Announce Type: new Abstract: Supervised Fine-Tuning (SFT) Large Language Models (LLM) fundamentally rely on high-quality training data. While data...
arXiv:2508.21206v1 Announce Type: new Abstract: Autoregressive language models are vulnerable to orthographic attacks, where input text is perturbed with characters...
arXiv:2507.05137v2 Announce Type: replace Abstract: Learning Japanese vocabulary is a challenge for learners from Roman alphabet backgrounds due to script...
arXiv:2406.06464v3 Announce Type: replace-cross Abstract: Deriving personalized insights from popular wearable trackers requires complex numerical reasoning that challenges standard LLMs,...
In this tutorial, we set out to recreate the spirit of the Hierarchical Reasoning Model (HRM) using a free Hugging...
Table of contents Introduction What is Tokenization? What is Chunking? The Key Differences That Matter Why This Matters for Real...
Modern large language models (LLMs) have moved far beyond simple text generation. Many of the most promising real-world applications now...
Table of contents The Problem with “Thinking Longer” The Agentic Approach Infrastructure Challenges and Solutions GRPO-RoC: Learning from High-Quality Examples...
This is the inside story of Intuit’s transformation journey with AI — including a grueling nine-month pivot to “burn the...
Agentar-Fin-R1: Enhancing Financial Intelligence through Domain Expertise, Training Efficiency, and Advanced Reasoning
Agent0: A Fully Autonomous AI Framework that Evolves High-Performing Agents without External Data through Multi-Step Co-Evolution
Agent-Dice: Disentangling Knowledge Updates via Geometric Consensus for Agent Continual Learning
Agent-based computing is outgrowing the web as we know it
Agent Learning via Early Experience
Agent confidence on the technical frontier
AgeLab research inspires an A I startup
AfriEconQA: A Benchmark Dataset for African Economic Analysis based on World Bank Reports
Afri-MCQA: Multimodal Cultural Question Answering for African Languages
AFA-LoRA: Enabling Non-Linear Adaptations in LoRA with Activation Function Annealing
