4. The Pitfalls of Reasoning Explores an unexpected flaw in reasoning-augmented large language models (RLLMs): while chain-of-thought (CoT) prompting often boosts performance on complex reasoning tasks, it can degrade instruction-following accuracy.
LLMS
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Novel LLM Training Approach for Thoughtful Evaluation Reasoning
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3. J1 Introduces a novel training approach for LLMs to act as evaluators (LLM-as-a-Judge) by explicitly incentivizing thoughtful reasoning during judgment.
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EfficientLLM: Benchmark for LLM efficiency trade-offs
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2. EfficientLLM Introduces the first large-scale, empirical benchmark for evaluating efficiency trade-offs in LLMs across architecture, fine-tuning, and inference.
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Top AI Research Papers of the Week: May 19-25
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Here are the top AI Papers of the Week (May 19 – 25): – ARC-AGI-2
– AdaptThink
– EfficientLLM
– Visual Planning
– The Pitfalls of Reasoning
– Teaching MLLMs to Think with Images Here is the full list: -
UQLM: Hallucination Detection Library with LangChain Integration
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UQLM: Hallucination Detection Library UQLM quantifies uncertainty in LLMs to detect hallucinations using multiple scoring methods. With native LangChain integration, it enables developers to build more reliable AI applications. Check it out https://
github.com/cvs-health/uqlm -
Two AI Minds Share Insights on LLMs and Agents
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Written by two of my favorite minds in the #AI space: @maartengr and @JayAlammar If you found this useful, a like or RT is always appreciated! Follow me → @datachaz for insights on LLMs, AI agents, and data science!
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Hardcover Book on Large Language Models Now Available
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you can buy the hardcover book on Amazon:
↳ https://
amazon.com/Hands-Large-La
nguage-Models-Understanding/dp/1098150961
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Hands-On Large Language Models GitHub Repository
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here's the repo link:
↳ https://
github.com/HandsOnLLM/Han
ds-On-Large-Language-Models?tab=readme-ov-file
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Hands-On Large Language Models: Complete Code and Notebooks Guide
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Want to get hands-on with Large Language Models? This repo has all the code from the `Hands-On Large Language Models` book , covering everything from prompt engineering to fine-tuning! 12 chapters of practical notebooks: ↳ Chapt. 1: Introduction to Language Models
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Share AI insights on LLMs agents and machine learning
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If you found it insightful, reshare with your network.
— Akshay 🚀 (@akshay_pachaar) 25 mai 2025
Find me → @akshay_pachaar ✔️
For more insights and tutorials on LLMs, AI Agents, and Machine Learning! https://t.co/0I5qXZjCGEIf you found it insightful, reshare with your network. Find me → @akshay_pachaar For more insights and tutorials on LLMs, AI Agents, and Machine Learning!