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LlamaCast

Shahriar Shariati

Daily podcast about the published articles in the LLM field.

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  • 20 episodes
  • Avg 16 min
  • English

Episodes 20

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  • S1 · E49
    Nov 23, 2024 · 14 min

    Marco-o1

    🤖 Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions The Alibaba MarcoPolo team presents Marco-o1, a large reasoning model designed to excel in open-ended problem-solving. Building upon OpenAI's o1 model, Marco-o1 incorporates...

  • S1 · E48
    Nov 18, 2024 · 18 min

    Scaling Laws for Precision

    ⚖️ Scaling Laws for Precision This research paper investigates the impact of precision in training and inference on the performance of large language models. The authors explore how precision affects the effective parameter count and propose scaling...

  • S1 · E47
    Nov 14, 2024 · 14 min

    Test-Time Training

    ⌛️ The Surprising Effectiveness of Test-Time Training for Abstract Reasoning This paper examines how test-time training (TTT) can enhance the abstract reasoning abilities of large language models (LLMs). TTT, which updates model parameters during...

  • S1 · E46
    Nov 12, 2024 · 24 min

    Qwen2.5-Coder

    🔷 Qwen2.5-Coder Technical Report The report introduces the Qwen2.5-Coder series, which includes the Qwen2.5-Coder-1.5B and Qwen2.5-Coder-7B models. These models are specifically designed for coding tasks and have been pre-trained on a massive dataset...

  • S1 · E45
    Nov 9, 2024 · 21 min

    Attacking Vision-Language Computer Agents via Pop-ups

    😈 Attacking Vision-Language Computer Agents via Pop-ups This research paper examines vulnerabilities in vision-language models (VLMs) that power autonomous agents performing computer tasks. The authors show that these VLM agents can be easily tricked...

  • S1 · E44
    Nov 8, 2024 · 16 min

    Number Cookbook

    📓 Number Cookbook: Number Understanding of Language Models and How to Improve It This research paper examines the numerical understanding and processing abilities (NUPA) of large language models (LLMs). The authors create a benchmark to test LLMs on...

  • S1 · E43
    Nov 7, 2024 · 16 min

    Jigsaw Puzzles

    🧩 Jigsaw Puzzles: Splitting Harmful Questions to Jailbreak Large Language Models This research paper investigates the vulnerabilities of large language models (LLMs) to "jailbreak" attacks, where malicious users attempt to trick the model into...

  • S1 · E42
    Nov 5, 2024 · 12 min

    Multi-expert Prompting with LLMs

    🤝 Multi-expert Prompting with LLMs The research paper presents Multi-expert Prompting, a novel method for improving the reliability, safety, and usefulness of Large Language Models (LLMs). Multi-expert Prompting simulates multiple experts within an...

  • S1 · E40
    Nov 2, 2024 · 16 min

    Mind Your Step (by Step)

    🌀 Mind Your Step (by Step): Chain-of-Thought can Reduce Performance on Tasks where Thinking Makes Humans Worse This research paper examines how chain-of-thought (CoT) prompting—encouraging models to reason step-by-step—affects large language and...

  • S1 · E39
    Oct 31, 2024 · 17 min

    SimpleQA

    ❓Measuring short-form factuality in large language models This document introduces SimpleQA, a new benchmark for evaluating the factuality of large language models. The benchmark consists of over 4,000 short, fact-seeking questions designed to be...

  • S1 · E38
    Oct 30, 2024 · 24 min

    GPT-4o System Card

    📜 GPT-4o System Card This technical document is the System Card for OpenAI's GPT-4o, a multimodal, autoregressive language model that can process and generate text, audio, images, and video. The card provides a detailed overview of the model's...

  • S1 · E37
    Oct 29, 2024 · 10 min

    Mixture of Parrots

    🦜 Mixture of Parrots: Experts improve memorization more than reasoning This research paper investigates the effectiveness of Mixture-of-Experts (MoE) architectures in deep learning, particularly comparing their performance to standard dense...

  • S1 · E36
    Oct 28, 2024 · 15 min

    Improve Vision Language Model Chain-of-thought Reasoning

    🖼 Improve Vision Language Model Chain-of-thought Reasoning This research paper investigates how to improve the chain-of-thought (CoT) reasoning capabilities of vision language models (VLMs). The authors address the lack of high-quality CoT data for...

  • S1 · E35
    Oct 27, 2024 · 15 min

    Breaking the Memory Barrier

    🧠 Breaking the Memory Barrier: Near Infinite Batch Size Scaling for Contrastive Loss This research paper introduces Inf-CL, a novel approach for contrastive learning that dramatically reduces GPU memory usage during training, allowing for...

  • S1 · E34
    Oct 26, 2024 · 11 min

    LLMs Reflect the Ideology of their Creators

    ⚖️ Large Language Models Reflect the Ideology of their Creators This study examines the ideological stances of large language models (LLMs) by analyzing their responses to prompts about a vast set of historical figures. The authors discovered that...

  • S1 · E33
    Oct 25, 2024 · 18 min

    LongRAG

    📜 LongRAG: A Dual-Perspective Retrieval-Augmented Generation Paradigm for Long-Context Question Answering The source is a research paper that proposes a new approach called LongRAG for enhancing the performance of Retrieval-Augmented Generation (RAG)...

  • S1 · E32
    Oct 24, 2024 · 9 min

    A Theoretical Understanding of Chain-of-Thought

    ⛓️ A Theoretical Understanding of Chain-of-Thought: Coherent Reasoning and Error-Aware Demonstration The paper explores Chain-of-Thought (CoT) prompting, a method to enhance the reasoning skills of large language models (LLMs). It introduces Coherent...

  • S1 · E31
    Oct 23, 2024 · 21 min

    A Survey on Data Synthesis and Augmentation for Large Language Models

    📚 A Survey on Data Synthesis and Augmentation for Large Language Models This research paper examines the use of synthetic and augmented data to enhance the capabilities of Large Language Models (LLMs). The authors argue that the rapid growth of LLMs...

  • S1 · E30
    Oct 22, 2024 · 8 min

    Revealing the Barriers of Language Agents in Planning

    🤔 Revealing the Barriers of Language Agents in Planning This research paper examines the challenges faced by language agents in planning tasks. The authors explore the reasons behind the shortcomings of these agents, particularly their limited...

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