That's my general view on all of this stuff now: the greatest misconception in LLMs is that the resulting tools are easy to use and to figure out
LLMS
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Aligning LLMs to Quote from Pre-Training Data
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9/ Aligning LLMs to Quote from Pre-Training Data – proposes techniques to align LLMs to leverage memorized information quotes directly from pre-training data.
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Iterative Self-Revision and Search for LLM Reasoning Tasks
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6/ Reasoning with Intermediate Revision and Search – presents an approach for general reasoning and search on tasks that can be decomposed into components; incorporates iterative self-revision capabilities and allows an LLM to build an interwoven network of thoughts.
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Multilingual LLMs Survey: Methods, Taxonomy and Research Frontiers
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7/ Overview of Multilingual LLMs – a survey on multilingual LLMs including a thorough review of methods, a taxonomy, emerging frontiers, challenges, and resources to advance research.
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Knowledge Capacity Scaling Laws in Language Models
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8/ The Physics of Language Models – investigates knowledge capacity scaling laws where it evaluates a model’s capability via loss or benchmarks, to estimate the number of knowledge bits a model stores.
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LM-Guided Chain-of-Thought Knowledge Distillation Technique
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4/ LM-Guided Chain-of-Thought – applies knowledge distillation to a small LM with rationales generated by the large LM; the rationale is then generated by the lightweight LM and the answer prediction is done by the frozen large LM.
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CodeGemma: Open Code LLM Family Matching Performance Benchmarks
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3/ CodeGemma – a family of open code LLMs based on Gemma; CodeGemma 7B models excel in mathematical reasoning and match the code capabilities of other open models.
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Discussion on the state of AI models and development tools
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Loads of new model releases but not many actual features & products lately. Should I cover more tools for AI development in the meantime? If yes, which tools are you using? Anyway, I have a Business trip to do next week. Gonna have some time to plan it better.
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Testing LLM Clients: httpx and pytest-httpx Best Practices
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Plus I like to write tests for my code, and figuring out how to serve a mock HTTP response to each different LLM client library in turn is a whole lot more work than just using httpx and pytest-httpx – which I already know
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Testing LLM Client Libraries with httpx and pytest-httpx
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Plus I like to write tests for my code, and figuring out how to serve a mock HTTP response to each different LLM client library in turn is a whole lot more work than just using httpx and pytest-httpx – which I already know