Bi'an: A Bilingual Benchmark and Model for Hallucination Detection in Retrieval-Augmented Generation Bi’an introduces a bilingual benchmark dataset (Bi’anBench) and lightweight judge models for hallucination detection in Retrieval-Augmented Generation (RAG). The dataset spans
MACHINE LEARNING
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SWE-RL: Enhancing LLM Reasoning Through Software Evolution
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SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution SWE-RL is a reinforcement learning (RL) approach that enhances LLM reasoning for software engineering by learning from open-source software evolution data. It trains Llama3-SWE-RL-70B on GitHub
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FFTNet: Efficient FFT-Based Alternative to Self-Attention
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The FFT Strikes Back: An Efficient Alternative to Self-Attention FFTNet replaces self-attention with an efficient O(n log n) spectral filtering approach using the Fast Fourier Transform (FFT). By operating in the frequency domain, it captures long-range dependencies while a
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AI Co-Scientist: Multi-Agent System for Scientific Hypothesis Generation
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Towards an AI co-scientist This paper introduces an AI co-scientist, a multi-agent system built on Gemini 2.0, designed to assist researchers by generating and refining novel scientific hypotheses. The system employs a "generate, debate, and evolve" framework to iteratively
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AI Co-Scientists and LLM Reasoning Advances This Week
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This week, AI is stepping into new dimensions—becoming co-scientists, sculpting 3D avatars, and blending cloud and on-device models into a seamless dance of creativity and efficiency. – Towards an AI co-scientist
– SWE-RL: Advancing LLM Reasoning via Reinforcement Learning -
Building Production-Ready RAG Systems with Qdrant FastAPI
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RAG Pipeline Guide Learn to build production-ready RAG systems using Qdrant vector DB, FastAPI, and LangChain's LCEL for sophisticated retrieval chains. Key features:
– Async vector search
– Type-safe FastAPI endpoints
– LCEL RAG pipelines Start building better RAG systems! -
LLMs Easily Influenced by Point-Based Games Through Reinforcement Learning
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Yes, quite well in fact. LLMs are very easily influenced by point-based games. It's an artifact of the reinforcement learning process
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MIT’s ‘Introduction to Algorithms’ Celebrates 30 Years As Premier CS Text
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MIT’s “Introduction to Algorithms,” published #otd in 1990, is the world’s most cited CS text, with 67K citations & over a million copies sold. https://
bit.ly/3y1yMPR @mitpress -
Economics of Artificial Intelligence: Automation’s Impact on Workers
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The Economics of Artificial Intelligence — What Does Automation Mean for Workers?
#AI #AIio #BigData #ML #NLU #Futureofwork @fabiomoioli @pascal_bornet @alliekmiller @mattshumer_ @OfficialLoganK @jeremyphoward @GaryMarcus -
LLMs, AI Agents, and ML/AI Engineering Tutorials
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That's a wrap! If you're interested in: – LLMs – AI Agents – ML/AI Engineering Find me →
@akshay_pachaar
Everyday, I share tutorials on above topics!