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I recently posted a paper whose theoretical derivations got an enormous amount of help from GPT (even though 5.6 Sol wasn’t out yet at the time). My senior labmate and I took the proof outline GPT gave us, refined it, and distilled the insights. Over the summer, I talked with a lot of people, and one question kept coming up: what is the point of theory, and where is its future?
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An interactive introduction to Pareto-frontier identification in multi-objective LLM arenas and adaptive sampling with VB-EGE.
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Retrieval strategies, count representations, causal interventions, and training dynamics in long-context counting.
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Implementation-first notes on optimizer geometry, AdamW, memory and distributed systems, and matrix-aware methods including SOAP and Muon.
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Implementation notes on byte-level BPE, fixed-tokenization failure modes, and dynamic byte-level models.
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Today is 2026.3.23, I finally have my personal homepage with the help of Codex!