Florence-VL A multimodal large language model (MLLM) that integrates enriched visual representations from Florence-2 for improved vision-language alignment. Problem: Existing vision-language models (VL) are limited by less versatile visual representations and the need for
LLMS
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Latest AI Papers: Navigation Models and Video Generation
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Trending AI papers on alphaXiv this week, featuring an incredible week for the computer vision and multimodal communities – Navigation World Models (discussion with author @_amirbar
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– Open-Sora Plan: Open-Source Large Generation Model (discussion with author -
Claude vs ChatGPT: Knowledge Cutoff Advantage Explained
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Why use #Claude over #ChatGPT? Claude’s got a knowledge cutoff that’s almost one year newer. In AI terms, that’s like a decade ahead, right?
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Large Language Models Demonstrate Self-Improvement Capabilities
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Large Language Models Can Self-Improve Huang et al.: https://
arxiv.org/abs/2210.11610 #ArtificialIntelligence #DeepLearning #MachineLearning -
Future LLMs as Justice Arbiters and Appeal Systems
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Concretely, imagine that the next generation of LLMs gets good enough to render judgments about justice. Then people want to appeal to it as arbiter, etc.
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Comparing iterative reasoning systems versus discrete program search efficiency
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Re: "optimal way to do reasoning". The idea here is that if you have an "iterated system 1" type reasoning system that takes ~$1k and O(hour) in compute to find a correct program to solve a simple task, vs. a discrete program search system that does the same in 0.1s on your
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WordPress categories focused on AI topics
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For anyone else reading along, tested this idea in a new post:
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Open Release Strategy for Flash 8B Model Discussed
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would y'all consider open release for flash 8B once the new generation kicks in?
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Discussion of CoT and model memorization/novelty
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Also, the reason for the light square condition is to inject arbitrary novelty, adding credence the solution isn’t memorized from training I’m not worried it is; in that 5m45s o1 spews out a dozen pages of CoT summary broadly consistent with its answer — representative excerpt:
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AI model ‘o1 pro’ hits limits and produces illegal chess positions
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This seems to be near the limit of what o1 pro can handle for this problem I first tried two pawns, two bishops, and a rook, but in four attempts o1 pro hit an error without returning and in the one that did, the position was not legal (both kings in check)