Krishnapriya Vishnubhotla
@krishnapriya-v22.bsky.social
PhD grad from UofT CompLing. Interested in narrative understanding, affective computing, language variation and style, and generally using NLP technologies to understand humans and society.
priya22.github.io
priya22.github.io
Reposted by Krishnapriya Vishnubhotla
ChatGPT + Post-Training
ChatGPT and The Art of Post-Training Barret Zoph & John Schulman
docs.google.com
March 18, 2025 at 9:05 PM
Reposted by Krishnapriya Vishnubhotla
Full Paper: arxiv.org/abs/2503.07513
Again, thanks to my amazing advisors @jennhu.bsky.social and @kmahowald.bsky.social for their guidance and support! (8/8)
Again, thanks to my amazing advisors @jennhu.bsky.social and @kmahowald.bsky.social for their guidance and support! (8/8)
Language Models Fail to Introspect About Their Knowledge of Language
There has been recent interest in whether large language models (LLMs) can introspect about their own internal states. Such abilities would make LLMs more interpretable, and also validate the use of s...
arxiv.org
March 12, 2025 at 2:31 PM
Full Paper: arxiv.org/abs/2503.07513
Again, thanks to my amazing advisors @jennhu.bsky.social and @kmahowald.bsky.social for their guidance and support! (8/8)
Again, thanks to my amazing advisors @jennhu.bsky.social and @kmahowald.bsky.social for their guidance and support! (8/8)
Yes, please!
March 12, 2025 at 4:19 AM
Yes, please!
Reposted by Krishnapriya Vishnubhotla
2.) [ICLR 2025]
When does CoT help? It turns out that gains are mainly on math and symbolic reasoning.
Check out our paper for a deep dive into MMLU, hundreds of experiments, and a meta-analysis of CoT across 3 conferences covering over 100 papers! arxiv.org/abs/2409.12183
When does CoT help? It turns out that gains are mainly on math and symbolic reasoning.
Check out our paper for a deep dive into MMLU, hundreds of experiments, and a meta-analysis of CoT across 3 conferences covering over 100 papers! arxiv.org/abs/2409.12183
To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning
Chain-of-thought (CoT) via prompting is the de facto method for eliciting reasoning capabilities from large language models (LLMs). But for what kinds of tasks is this extra ``thinking'' really helpfu...
arxiv.org
March 11, 2025 at 10:03 PM
2.) [ICLR 2025]
When does CoT help? It turns out that gains are mainly on math and symbolic reasoning.
Check out our paper for a deep dive into MMLU, hundreds of experiments, and a meta-analysis of CoT across 3 conferences covering over 100 papers! arxiv.org/abs/2409.12183
When does CoT help? It turns out that gains are mainly on math and symbolic reasoning.
Check out our paper for a deep dive into MMLU, hundreds of experiments, and a meta-analysis of CoT across 3 conferences covering over 100 papers! arxiv.org/abs/2409.12183
Reposted by Krishnapriya Vishnubhotla
Wild how long it took someone to actually test this, but it's natural given how disconnected most interp neophytes are from the history of the field. Reminder that @sarah-nlp.bsky.social and I wrote a history of LM interpretability for the NLP and mech interp communities 👀
Mechanistic?
The rise of the term "mechanistic interpretability" has accompanied increasing interest in understanding neural models -- particularly language models. However, this jargon has also led to a fair amou...
arxiv.org
March 3, 2025 at 6:51 PM
Wild how long it took someone to actually test this, but it's natural given how disconnected most interp neophytes are from the history of the field. Reminder that @sarah-nlp.bsky.social and I wrote a history of LM interpretability for the NLP and mech interp communities 👀