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X X^t can be faster(arxiv.org)
188 points by robinhouston | 57 comments
LLMs should not replace therapists(arxiv.org)
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LLMs use a surprisingly simple mechanism to retrieve some stored knowledge(news.mit.edu)
336 points by CharlesW | 121 comments
MIT News article on research showing LLMs often retrieve stored facts via simple linear functions, and a technique to probe what a model knows about subjects.
Better Call GPT: Comparing large language models against lawyers [pdf](arxiv.org)
347 points by vinnyglennon | 236 comments
arXiv paper comparing large language models with junior lawyers and legal process outsourcers on contract review accuracy, speed, and cost.
LIMO: Less Is More for Reasoning(arxiv.org)
376 points by trott | 126 comments
arXiv paper presenting LIMO, a model showing complex math reasoning in LLMs can be elicited with only 817 curated training samples.
2025: The Year in LLMs(simonwillison.net)
823 points by simonw | 451 comments
Simon Willison's annual blog post reviewing major LLM trends of 2025, including reasoning models, coding agents, Chinese open weight models, and Gemini.
Ladder: Self-improving LLMs through recursive problem decomposition(arxiv.org)
339 points by fofoz | 103 comments
arXiv paper introducing LADDER, a framework where LLMs self-improve by recursively generating simpler problem variants, plus TTRL test-time reinforcement learning.
Publish fake stats, get cited in LLMs(peec.ai)
315 points by robtherobber | 204 comments
Peec AI blog post by a GEO researcher describing how publishing statistics led to the author's data being widely cited across the web and by LLMs.








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