IRIX Introduction
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Show HN: Pipeflow-PHP – Automate anything with pipelines even non-devs can edit
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Causal Graph Neural Networks for Healthcare
arxiv.org·5d
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MeixnerNet: Adaptive and Robust Spectral Graph Neural Networks with Discrete Orthogonal Polynomials
arxiv.org·6d
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Advancing AI Challenges for the United States Department of the Air Force
arxiv.org·6d
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FLoRA: Fused forward-backward adapters for parameter efficient fine-tuning and reducing inference-time latencies of LLMs
arxiv.org·6d
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One Shot Singalonging is an attitude, not a skill or song-difficulty-level
lesswrong.com·1d
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Performance Analysis of NOMA-Assisted Optical OFDM ISAC Systems with Clipping Distortion
arxiv.org·5d
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Magnetic Materials for Transcranial Magnetic Stimulation (TMS)
arxiv.org·6d
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Condition-Invariant fMRI Decoding of Speech Intelligibility with Deep State Space Model
arxiv.org·5d
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Autobiasing Event Cameras for Flickering Mitigation
arxiv.org·5d
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Adaptive Neighborhood-Constrained Q Learning for Offline Reinforcement Learning
arxiv.org·5d
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Defining Energy Indicators for Impact Identification on Aerospace Composites: A Physics-Informed Machine Learning Perspective
arxiv.org·6d
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LLMs Position Themselves as More Rational Than Humans: Emergence of AI Self-Awareness Measured Through Game Theory
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What's the stack for going from a fine-tune on vLLM to a simple, paid public API?
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I made a complete tutorial on fine-tuning Qwen2.5 (1.5B) on a free Colab T4 GPU. Accuracy boosted from 91% to 98% in ~20 mins!
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Modeling Hawkish-Dovish Latent Beliefs in Multi-Agent Debate-Based LLMs for Monetary Policy Decision Classification
arxiv.org·5d
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Training LLMs Beyond Next Token Prediction - Filling the Mutual Information Gap
arxiv.org·6d
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