Vighnesh Subramaniam

18 posts

Vighnesh Subramaniam

Vighnesh Subramaniam

@su1001v

PhD student @ MIT EECS + @MIT_CSAIL https://t.co/UDgL88atg9

Katılım Ocak 2024
83 Takip Edilen105 Takipçiler
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Vighnesh Subramaniam
Vighnesh Subramaniam@su1001v·
Excited to announce that I'll be presenting Training the Untrainable at #NeurIPS2025 ! Come say hello :) or DM/email if you want to chat. untrainable-networks.github.io Also keep on the look out for some really exciting new work in the pipeline coming very soon... 👀👀
Vighnesh Subramaniam@su1001v

New paper💡! Certain networks can't perform certain tasks due to lacking the right prior 😢. Can we make these untrainable networks trainable 🤔? We can, by introducing the prior through representational alignment with a trainable network! This approach is called guidance. (1/8)

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Phillip Isola
Phillip Isola@phillip_isola·
Impromptu NeurIPS meetup: "representational convergence by the beach." We will meet at ballroom 20c (near lunch) 2pm Fri and walk over to Marina. Will chat about platonic reps, fractured reps, or anything else about where all these models are heading. Anyone is welcome to join!
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Kathy Garcia
Kathy Garcia@NeuroKathyG·
Excited to share that I’m at #NeurIPS2025 this year! 🧠 I’ll be presenting at the UniReps Workshop on my work on Social Tokens with @su1001v and @thisismyhat, where we explore how to inject socially relevant visual features into language models to improve social reasoning and alignment. Super excited to connect with folks working at the intersection of multimodal models and human cognition. If you’re around, come say hi! And feel free to DM me for a coffee chat ☕️
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Christopher Wang
Christopher Wang@czlwang·
Want to scale models on brain datasets recorded with variable sensor layouts? Population Transformer at #ICLR2025 may be your answer! 🗺️ Fri, Apr 25 | 10am - 12:30pm (poster @ Hall 3 + Hall 2B #58) 🗣️ Fri, Apr 25 | 4:06 pm - 4:18 pm (oral @ Garnet 216-218) More ⬇️
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Vighnesh Subramaniam
Vighnesh Subramaniam@su1001v·
Check out our new work for self-improvement of LLMs! This work uses a multi-agent set up that not only improves performance but preserves diversity over iterations of finetuning. Website: llm-multiagent-ft.github.io Paper: arxiv.org/abs/2501.05707
Yilun Du@du_yilun

Introducing multi-agent self-improvement with LLMs! llm-multiagent-ft.github.io Instead of self improving a single LLM, we self-improve a population of LLMs initialized from a base model. This enables consistent self-improvement over multiple rounds.

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Andrei Barbu
Andrei Barbu@_abarbu_·
Interested in large-scale neuroscience of language and multimodal representations? We have the dataset for you, the Brain Treebank! Come to our oral at NeurIPS. Today at 3:50pm PST, East Meeting room braintreebank.dev Now with extra foundation models arxiv.org/abs/2302.14367
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Vighnesh Subramaniam
Vighnesh Subramaniam@su1001v·
We cover tons of other experiments and settings in the paper such as stopping guidance early and analyzing error consistency of guided networks in the paper. We hope guidance can be a general tool for improving and understanding neural network design😀! (7/8)
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Vighnesh Subramaniam
Vighnesh Subramaniam@su1001v·
New paper💡! Certain networks can't perform certain tasks due to lacking the right prior 😢. Can we make these untrainable networks trainable 🤔? We can, by introducing the prior through representational alignment with a trainable network! This approach is called guidance. (1/8)
Vighnesh Subramaniam tweet media
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Geeling Chau
Geeling Chau@GeelingC·
How can we train models on more brains and sensor layouts? We present Population Transformer (PopT) which learns population-level interactions on intracranial electrodes, with 🔥decoding and interpretability benefits. See our poster at #ICML2024 @AI_for_Science 12pm
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