Elliot Murphy (@ElliotMurphy91) header
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• Postdoc, Department of Neurosurgery, UTHealth • Neural mechanisms of compositional syntax

Houston, TX
Joined May 2026
Photo by Elliot Murphy (@ElliotMurphy91)Photo by Elliot Murphy (@ElliotMurphy91)Photo by Elliot Murphy (@ElliotMurphy91)Photo by Elliot Murphy (@ElliotMurphy91)Photo by Elliot Murphy (@ElliotMurphy91)Photo by Elliot Murphy (@ElliotMurphy91)Photo by Elliot Murphy (@ElliotMurphy91)Photo by Elliot Murphy (@ElliotMurphy91)Photo by Elliot Murphy (@ElliotMurphy91)Photo by Elliot Murphy (@ElliotMurphy91)
New work out today! The result of a 15 year project to offer genuine linking hypotheses between language & brain: a revised research program, and its first result - a novel neural binding operation ('Meld') capturing core properties of syntax 🧵 arxiv.org/abs/2609.14384
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Recursion in the wild
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Elliot Murphy retweeted
The video for "Merge: Past, Present, and Future" is now out. ordinaryworkinggrammarian.bl…
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This is an old hat. That's exactly what the neural fast weight programmers did in the 1990s (including the 1991 unnormalised linear Transformer). Overview with links to the original papers: people.idsia.ch/~juergen/fas…
We asked GPT-6 Astra to edit Qwen3.5-0.8B weights to improve math. It directly changed only 0.016% of weights, fixing 0.8B's reasoning loops & improving math up to 6x and even instruction following 3x, without gradients or training. We call this Weight-Space Programming: frontier LLMs can now natively read/write neural network weights! 🧵 Blog: rikiyat.github.io/blog/weigh…
Readers added context they thought people might want to know
LLM was given weights explicitly as text in prompt and used code/forward passes (per authors' logs) to ablate Qwen looping direction, a known thinking-mode issue per model card. Primarily fixed repetition in that mode, not general 'natively' improving weights/math. rikiyat.github.io/blog/weight-sp… github.com/RikiyaT/lm_und… huggingface.co/Qwen/Qwen3.5-0… huggingface.co/RikiyaT/Qwen3.…
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How long does a finding about LLMs stay true? We re-tested 50 widely cited findings about LLM behavior (various biases, hallucination, etc). Within 15 months, most no longer held or had substantially reduced effects. LLM findings has short shelf life zou-group.github.io/llm-clai… Great job by @oq_35!
1/n Within 15 months of publication, most of the LLM claims we tested either no longer held or showed substantially diminished effects. How long does our knowledge of AI hold up? In our new study, we revisit 50 findings to see what fades, what persists, and what gets stronger. 🧵
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Following up this, a new preprint from my lab finds a human cousin with iEEG recordings: when an identical sound is presented but creates a different percept due to expectation, we see a rhythmic interplay of brain wave activity reflecting the mismatch: biorxiv.org/content/10.64898…
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“Our results … cast doubt on the claim that transformers represent sentence meaning similarly to the human brain.”
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I'm giving a talk on the power of language this Thursday (10/22) at 3:30pm (New York time). It's on Zoom, so feel free to join!
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Three reasons why AI is extremely unlikely to be conscious - and why this matters. Joint opinion in @nature with Giulio Tononi and Ned Block @De_dicto
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Assessing agrammatic speech: Insights from perceptual ratings, statistical metrics, and lesion-symptom mapping sciencedirect.com/science/ar…
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New paper out today! We extend Rational Speech Act models using coupled active inference. A number of clear implications for theories of pragmatics and the language/thought debate follow 🧵 arxiv.org/abs/2610.04347
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