Phelim Bradley’s Post

Say hello to expanded representative sample sizes, enhanced LLM-text detection verification, and the introduction of verified domain expert participants on Prolific! What's New? 📈 Expanded Representative Sample Sizes: We've doubled our pool sizes for UK and US political rep samples, allowing for quicker, more comprehensive studies. 🤖 LLM-Text Detection Verification: Our new detection approach ensures the authenticity of our human data by rigorously checking for LLM-generated texts. 🧠 Verified Experts: Soon, you'll have access to a pool of research participants with verifiable expert skills, from coding to multilingual communication. Whether you're conducting studies focused on the UK or US political landscapes or in need of participants with specialized skills, our latest features ensure that your research is both expansive and representative. Want to find out more? Read our new blog post ⬇️ https://lnkd.in/eXzZN3zZ

💎 𝐓𝐡𝐞 𝐀𝐫𝐭 𝐨𝐟 𝐑𝐞𝐟𝐮𝐬𝐚𝐥 𝐢𝐧 𝐋𝐋𝐌𝐬: 𝐀 𝐒𝐮𝐫𝐯𝐞𝐲 ✅ Abstention, the refusal of large language models (LLMs) to provide an answer, is increasingly recognized for its potential to mitigate hallucinations and enhance safety in building LLM systems. ✅ This survey introduces a framework to examine abstention behavior. 👉 https://lnkd.in/dbjvcGUR ♻️𝒌𝒊𝒏𝒅𝒍𝒚 𝒓𝒆𝒑𝒐𝒔𝒕♻️

Learn how RAG gives LLMs real-time learning without re-training. The soup that eats like a meal. #artificialintelligence #emergingtechnologies

LLM Contributor Projects Week - LLM Debate 📚 Ogban Ugot and Sanjay Suthar have been working on LLM Debate. Try it out! - https://lnkd.in/eAMAc4VY In this project, they developed a web application that allows two LLMs to engage in a real-time conversation on a topic chosen by the user. Users can select any two models, input a query, and view the dialogue between the LLMs as it unfolds. This application, built using Unify and deployed with Streamlit, offers a platform for users to observe AI-generated debates and explore the capabilities of different language models ⚡ ⚔ Check out their presentation - https://lnkd.in/e8z_3RzG Check out the repo here - https://lnkd.in/eaenqth7

Listening to a great webinar. Hope you have a chance to review the newest language access material at DOJ. https://lnkd.in/gQTYfNyv

A new topic is here on TEKnically Speaking this week! What is RAG? Well, it's definitely easier to say than Retrieval-Augmented Generation. In short, this week's topic relates to large language models and bringing their data up-to-date. But Mark and Ned will explain it better than we can. Mark Campbell, Chief Innovation Officer, EVOTEK Ned Engelke, Chief Technology Officer, EVOTEK https://hubs.la/Q02rTYDh0

A new topic is here on TEKnically Speaking this week! What is RAG? Well, it's definitely easier to say than Retrieval-Augmented Generation. In short, this week's topic relates to large language models and bringing their data up-to-date. But Mark and Ned will explain it better than we can. Mark Campbell, Chief Innovation Officer, EVOTEK Ned Engelke, Chief Technology Officer, EVOTEK https://hubs.la/Q02rTZl10

A new topic is here on TEKnically Speaking this week! What is RAG? Well, it's definitely easier to say than Retrieval-Augmented Generation. In short, this week's topic relates to large language models and bringing their data up-to-date. But Mark and Ned will explain it better than we can. Mark Campbell, Chief Innovation Officer, EVOTEK Ned Engelke, Chief Technology Officer, EVOTEK https://hubs.la/Q02rT_Zh0

🔍 Exciting News! Our latest blog post introduces the Polish Information Retrieval Benchmark (PIRB), a comprehensive evaluation framework covering 41 text information retrieval tasks for Polish. The benchmark includes 10 new, previously unpublished datasets across various domains. We evaluated over 20 retrieval models, including dense and sparse methods, and introduced a three-step process for training highly effective language-specific retrievers. Our findings show that our dense models outperform existing solutions, and the use of hybrid methods further enhances their performance. Read more at https://bit.ly/3wmIS09 #InformationRetrieval #PolishLanguage #Benchmarking

Weekend Agent Reasoning List ⎆ On the Diagram of Thought[ https://buff.ly/3ZBM3he ] ⎆ Iteration of Thought: Leveraging Inner Dialogue for Autonomous Large Language Model Reasoning[https://buff.ly/3XLJJBN ] ⎆ Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models [https://buff.ly/4ekwY8m ] ⎆ Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation[https://buff.ly/3zBoEll ] Like, repost, and share this with your friends to show the best papers. For paper implementations, open source projects, and paper discussions join the agora discord now:

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