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Aryaman Arora
14.2K posts
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Aryaman Arora
@aryaman2020
member of technical staff @stanfordnlp
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aryaman.io
Joined December 2018
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  • user avatar
    Aryaman Arora
    @aryaman2020
    Jun 14, 2025
    Claude
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    Image
    459K
  • user avatar
    Aryaman Arora
    @aryaman2020
    Jan 15, 2025
    clown post. everyone who has ever touched an LLM should literally be worshipping wikipedia
    This post is unavailable.
    284K
  • user avatar
    Aryaman Arora
    @aryaman2020
    Oct 16, 2022
    I updated my interactive South Asian language census map to include tehsil-level data from India (2011) and Pakistan (2017) and subdivision-level data from Nepal (2011). aryamanarora.github.io/india-census-2…
    Language map of India, Pakistan, Nepal, and (kinda) Bangladesh. A lot of colours demonstrating a lot of linguistic diversity.
  • user avatar
    Aryaman Arora
    @aryaman2020
    Mar 29, 2024
    Replying to @jxmnop
    Noam Shazeer wrote down each pixel manually in vim
    63K
  • user avatar
    Aryaman Arora
    @aryaman2020
    Aug 1, 2024
    8x NVIDIA H100 80GB
    user avatar
    Dr. Jessica Vitak, Privacy Zealot
    @jvitak
    Jul 31, 2024
    Folks who have completed or are currently doing their PhD: If you were to have received a small welcome packet at your desk on Day 1 of your PhD, what would you want it to include? Some ideas: Post-its, a fun pen, highlighters, stapler, candy. What else?
    44K
  • user avatar
    Aryaman Arora
    @aryaman2020
    Jul 22, 2025
    if you think data cleaning is beneath you then ngmi
    user avatar
    Luke Heeney
    @heeney_luke
    Jul 18, 2025
    Academia must be the only industry where extremely high-skilled PhD students spend much of their time doing low value work (like data cleaning). A 1st year management consultant outsources this immediately. Imagine the productivity gains if PhDs could focus on thinking
    34K
  • user avatar
    Aryaman Arora
    @aryaman2020
    May 28, 2025
    new paper! 🫡 why are state space models (SSMs) worse than Transformers at recall over their context? this is a question about the mechanisms underlying model behaviour: therefore, we propose using mechanistic evaluations to answer it!
    Image
    81K
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    Aryaman Arora
    @aryaman2020
    Oct 31, 2024
    New paper! 🫡 In-context learning (ICL) is when LLMs infer how to do a task from examples. We know that the relationship between # of ICL examples and task accuracy is predictable. Can we predict the shape of the ICL curve using Bayesian assumptions? Our paper shows yes!
    paper title page
    98K
  • user avatar
    Aryaman Arora
    @aryaman2020
    Apr 5, 2024
    New paper! 🫡 We introduce Representation Finetuning (ReFT), a framework for powerful, efficient, and interpretable finetuning of LMs by learning interventions on representations. We match/surpass PEFTs on commonsense, math, instruct-tuning, and NLU with 10–50× fewer parameters.
    Figure 1: Parameter count vs. performance for LoReFT and other PEFTs across four benchmarks
when applied to LLaMA, Llama-2, and RoBERTa models. Despite training much fewer parameters
than existing PEFTs, LoReFT achieves competitive or even state-of-the-art performance on all tasks.
Its value is most apparent for the largest models in our evaluations. Note: FT refers to full-parameter
finetuning, which is not a PEFT or ReFT method.
    105K
  • user avatar
    Aryaman Arora
    @aryaman2020
    Mar 25, 2023
    So, committed to Stanford to start my Ph.D. in CS in the fall 😮
    98K
  • user avatar
    Aryaman Arora
    @aryaman2020
    Sep 14, 2024
    I think Karpathy is super wrong on this. Text is an amazingly efficient medium for compressing meaning. Images have like no useful info content in comparison
    user avatar
    Andrej Karpathy
    @karpathy
    Sep 14, 2024
    It's a bit sad and confusing that LLMs ("Large Language Models") have little to do with language; It's just historical. They are highly general purpose technology for statistical modeling of token streams. A better name would be Autoregressive Transformers or something. They
    132K
  • user avatar
    Aryaman Arora
    @aryaman2020
    Nov 12, 2025
    i hate ML conference reviewers. i take back everything bad i ever said about ACL. every ACL reviewer i ever got was at least literate
    36K
  • user avatar
    Aryaman Arora
    @aryaman2020
    Nov 13, 2025
    i cannot overstate how absurdly impressive stanford's rl infra is the people working on it clearly view it as art and actually barely get paid if you like rl, there’s really no better place on earth to work on it
    user avatar
    Aidan McLaughlin
    @aidan_mclau
    Nov 12, 2025
    i cannot overstate how absurdly impressive openai’s rl infra is the people working on it clearly view it as art and probably forget they get paid if you like rl, there’s really no better place on earth to work on it
    81K
  • user avatar
    Aryaman Arora
    @aryaman2020
    Jan 30, 2025
    new paper! 🫡 we introduce 🪓AxBench, a scalable benchmark that evaluates interpretability techniques on two axes: concept detection and model steering. we find that: 🥇prompting and finetuning are still best 🥈supervised interp methods are effective 😮SAEs lag behind
    Image
    105K

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