565 citations · 766 across the 31 of their papers we have counts for
35 papers
BuzzASR: A Swarm of 100+ Monolingual Speech Recognition Models
Shivam Singh, Aditya Yadavalli, Catherine Arnett +1
We introduce BuzzASR, a collection of language-specialized fine-tuned Whisper models adapted for automatic speech recognition (ASR) in 102 languages. Large end-to-end Transformer-b…
Using Prosody to Predict Syntactic Structure
Junghyun Min, Alex Warstadt, Tamar I. Regev +2
While it is well-established that prosody carries crucial cues for syntactic structure, the degree and nature of correspondence between these two domains remains contested. We inve…
It's Not What You Say, It's How You Say It: Evaluating LLM Responses to Expressions of Belief
Kevin Du, Clara Kümpel, Michelle Wastl +1
Users frequently express their beliefs to large language models (LLMs). In some situations, the LLM should accept these contextual beliefs as true. In others, they should stick to…
What Do Prosody and Text Convey? Characterizing How Meaningful Information is Distributed Across Multiple Channels
Aditya Yadavalli, Tiago Pimentel, Tamar I Regev +2
Prosody -- the melody of speech -- conveys critical information often not captured by the words or text of a message. In this paper, we propose an information-theoretic approach to…
Using Information Theory to Characterize Prosodic Typology: The Case of Tone, Pitch-Accent and Stress-Accent
Ethan Gotlieb Wilcox, Cui Ding, Giovanni Acampa +3
This paper argues that the relationship between lexical identity and prosody -- one well-studied parameter of linguistic variation -- can be characterized using information theory.…
Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora
Alex Warstadt, Aaron Mueller, Leshem Choshen +8
Children can acquire language from less than 100 million words of input. Large language models are far less data-efficient: they typically require 3 or 4 orders of magnitude more d…
The time scale of redundancy between prosody and linguistic context
Tamar I. Regev, Chiebuka Ohams, Shaylee Xie +5
In spoken communication, information is transmitted not only via words, but also through a rich array of non-verbal signals, including prosody--the non-segmental auditory features…
Surprise! Uniform Information Density Isn't the Whole Story: Predicting Surprisal Contours in Long-form Discourse
Eleftheria Tsipidi, Franz Nowak, Ryan Cotterell +3
The Uniform Information Density (UID) hypothesis posits that speakers tend to distribute information evenly across linguistic units to achieve efficient communication. Of course, i…
Investigating Critical Period Effects in Language Acquisition through Neural Language Models
Ionut Constantinescu, Tiago Pimentel, Ryan Cotterell +1
Humans appear to have a critical period (CP) for language acquisition: Second language (L2) acquisition becomes harder after early childhood, and ceasing exposure to a first langua…
Rel-A.I.: An Interaction-Centered Approach To Measuring Human-LM Reliance
Kaitlyn Zhou, Jena D. Hwang, Xiang Ren +3
The ability to communicate uncertainty, risk, and limitation is crucial for the safety of large language models. However, current evaluations of these abilities rely on simple cali…
[Call for Papers] The 2nd BabyLM Challenge: Sample-efficient pretraining on a developmentally plausible corpus
Leshem Choshen, Ryan Cotterell, Michael Y. Hu +7
After last year's successful BabyLM Challenge, the competition will be hosted again in 2024/2025. The overarching goals of the challenge remain the same; however, some of the compe…
Automatic Annotation of Grammaticality in Child-Caregiver Conversations
Mitja Nikolaus, Abhishek Agrawal, Petros Kaklamanis +2
The acquisition of grammar has been a central question to adjudicate between theories of language acquisition. In order to conduct faster, more reproducible, and larger-scale corpu…
WhisBERT: Multimodal Text-Audio Language Modeling on 100M Words
Lukas Wolf, Greta Tuckute, Klemen Kotar +4
Training on multiple modalities of input can augment the capabilities of a language model. Here, we ask whether such a training regime can improve the quality and efficiency of the…
Quantifying the redundancy between prosody and text
Lukas Wolf, Tiago Pimentel, Evelina Fedorenko +4
Prosody -- the suprasegmental component of speech, including pitch, loudness, and tempo -- carries critical aspects of meaning. However, the relationship between the information co…
Generalizing Backpropagation for Gradient-Based Interpretability
Kevin Du, Lucas Torroba Hennigen, Niklas Stoehr +2
Many popular feature-attribution methods for interpreting deep neural networks rely on computing the gradients of a model's output with respect to its inputs. While these methods c…
A Geometric Notion of Causal Probing
Clément Guerner, Tianyu Liu, Anej Svete +2
The linear subspace hypothesis (Bolukbasi et al., 2016) states that, in a language model's representation space, all information about a concept such as verbal number is encoded in…
Call for Papers -- The BabyLM Challenge: Sample-efficient pretraining on a developmentally plausible corpus
Alex Warstadt, Leshem Choshen, Aaron Mueller +3
We present the call for papers for the BabyLM Challenge: Sample-efficient pretraining on a developmentally plausible corpus. This shared task is intended for participants with an i…
Reconstruction Probing
Najoung Kim, Jatin Khilnani, Alex Warstadt +1
We propose reconstruction probing, a new analysis method for contextualized representations based on reconstruction probabilities in masked language models (MLMs). This method reli…
Entailment Semantics Can Be Extracted from an Ideal Language Model
William Merrill, Alex Warstadt, Tal Linzen
Language models are often trained on text alone, without additional grounding. There is debate as to how much of natural language semantics can be inferred from such a procedure. W…
What Artificial Neural Networks Can Tell Us About Human Language Acquisition
Alex Warstadt, Samuel R. Bowman
Rapid progress in machine learning for natural language processing has the potential to transform debates about how humans learn language. However, the learning environments and bi…
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao +448
Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabil…
What Makes Reading Comprehension Questions Difficult?
Saku Sugawara, Nikita Nangia, Alex Warstadt +1
For a natural language understanding benchmark to be useful in research, it has to consist of examples that are diverse and difficult enough to discriminate among current and near-…
NOPE: A Corpus of Naturally-Occurring Presuppositions in English
Alicia Parrish, Sebastian Schuster, Alex Warstadt +5
Understanding language requires grasping not only the overtly stated content, but also making inferences about things that were left unsaid. These inferences include presupposition…
What Ingredients Make for an Effective Crowdsourcing Protocol for Difficult NLU Data Collection Tasks?
Nikita Nangia, Saku Sugawara, Harsh Trivedi +3
Crowdsourcing is widely used to create data for common natural language understanding tasks. Despite the importance of these datasets for measuring and refining model understanding…