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RESEARCH
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Data Engineering’s Critical Role in AI Revolution and Real-Time Insights
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Visual guide to copulas for machine learning applications
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while my_mcmc: gently(samples) – An intuitive, visual guide to copulas https://
bit.ly/3Y7zzwL
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Join AI Generative Community in California Desert
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If you are:
– an artist, researcher, or indiehacker deep into generative AI.
– crave studying it in an IRL community in a beautiful location.
– want/need to get off the hamster wheel of making rent in SF/NYC. This is where you should go. Join us in the California desert, Jan-Apr -
OpenAI o1 Models Planning Abilities Self-Evaluation Constraints
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9). On the Planning Abilities of OpenAI’s o1 Models – reports that o1-preview is particularly strong in self-evaluation and constraint-following; also mentions that these o1 models demonstrate bottlenecks in decision-making and memory management, which are more pronounced in
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CoTracker3: Semi-Supervised Point Tracking Model with Pseudo-Labels
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10). CoTracker3 – proposes a new point tracking model and a new semi-supervised training recipe; enables usage of real videos without annotations during training by generating pseudo-labels using off-the-shelf teachers.https://t.co/vCbJzcXSPj
— DAIR.AI (@dair_ai) 20 octobre 202410). CoTracker3 – proposes a new point tracking model and a new semi-supervised training recipe; enables usage of real videos without annotations during training by generating pseudo-labels using off-the-shelf teachers.
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Model Kinship Strategy for Improved LLM Merging
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8). Model Kinship for Merging LLMs – proposes model kinship to measure the degree of similarity between LLMs; model kinship is used to build a model merging strategy (Top-k Greedy Merging with Model Kinship) which yields better performance.
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Inference Scaling Laws for Long-Context RAG Systems
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6). Inference Scaling for Long-Context RAG – uses two strategies to investigate scaling laws for RAG: in-context learning and iterative prompting; RAG performance improves with the expansion of the effective context length under optimal configurations.
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Janus: Unified Autoregressive Framework for Multimodal Understanding
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5). Janus – proposes a unified autoregressive framework for multimodal understanding and generation; it decouples visual encoding into independent pathways and leverages a single transformer architecture to improve flexibility and performance on both visual understanding and
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First-Person Fairness Biases in ChatGPT Analysis
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3). First-Person Fairness in Chatbots – studies first-person fairness which involves fairness towards users interacting with ChatGPT; specifically, it measures the biases, if any, towards the users’ names…
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LLM Introspection Enables Self-Knowledge and System Interpretability
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4). Introspection in LLMs – reports that LLMs can acquire knowledge through introspection that cannot be inferred from their training data; suggests that LLMs contain privileged information about themselves that can potentially lead to more interpretable and controllable systems.