2 citations · 3 across the 2 of their papers we have counts for
5 papers
Do LLMs Really Need 10+ Thoughts for "Find the Time 1000 Days Later"? Towards Structural Understanding of LLM Overthinking
Xinliang Frederick Zhang, Anhad Mohananey, Alexandra Chronopoulou +5
Models employing long chain-of-thought (CoT) reasoning have shown superior performance on complex reasoning tasks. Yet, this capability introduces a critical and often overlooked i…
Fact, Fetch, and Reason: A Unified Evaluation of Retrieval-Augmented Generation
Satyapriya Krishna, Kalpesh Krishna, Anhad Mohananey +4
Large Language Models (LLMs) have demonstrated significant performance improvements across various cognitive tasks. An emerging application is using LLMs to enhance retrieval-augme…
Self-Training for Unsupervised Parsing with PRPN
Anhad Mohananey, Katharina Kann, Samuel R. Bowman
Neural unsupervised parsing (UP) models learn to parse without access to syntactic annotations, while being optimized for another task like language modeling. In this work, we prop…
BLiMP: The Benchmark of Linguistic Minimal Pairs for English
Alex Warstadt, Alicia Parrish, Haokun Liu +4
We introduce The Benchmark of Linguistic Minimal Pairs (shortened to BLiMP), a challenge set for evaluating what language models (LMs) know about major grammatical phenomena in Eng…
Investigating BERT's Knowledge of Language: Five Analysis Methods with NPIs
Alex Warstadt, Yu Cao, Ioana Grosu +13
Though state-of-the-art sentence representation models can perform tasks requiring significant knowledge of grammar, it is an open question how best to evaluate their grammatical k…