38 citations · 51 across the 26 of their papers we have counts for
26 papers
Linguistic Distancing on Social Media: Indicators of Emotion Regulation Across Age Groups
Daniela Teodorescu, Saif M. Mohammad, Alona Fyshe
Managing our emotional responses to events is key to emotional well-being, a process referred to as emotion regulation in psychology. Previous work has established that the degree…
Understanding the Staged Dynamics of Transformers in Learning Latent Structure
Rohan Saha, Farzane Aminmansour, Alona Fyshe
Language modeling has shown us that transformers can discover latent structure from context, but the dynamics of how they acquire different components of that structure remain poor…
Offline Preference Optimization via Maximum Marginal Likelihood Estimation
Saeed Najafi, Alona Fyshe
Aligning Large Language Models (LLMs) with human preferences is crucial, but standard methods like Reinforcement Learning from Human Feedback (RLHF) are often complex and unstable.…
Exploring Curriculum Learning for Vision-Language Tasks: A Study on Small-Scale Multimodal Training
Rohan Saha, Abrar Fahim, Alona Fyshe +1
For specialized domains, there is often not a wealth of data with which to train large machine learning models. In such limited data / compute settings, various methods exist aimin…
It's Not a Modality Gap: Characterizing and Addressing the Contrastive Gap
Abrar Fahim, Alex Murphy, Alona Fyshe
Multi-modal contrastive models such as CLIP achieve state-of-the-art performance in zero-shot classification by embedding input images and texts on a joint representational space.…
Correcting Biased Centered Kernel Alignment Measures in Biological and Artificial Neural Networks
Alex Murphy, Joel Zylberberg, Alona Fyshe
Centred Kernel Alignment (CKA) has recently emerged as a popular metric to compare activations from biological and artificial neural networks (ANNs) in order to quantify the alignm…
Finding Shared Decodable Concepts and their Negations in the Brain
Cory Efird, Alex Murphy, Joel Zylberberg +1
Prior work has offered evidence for functional localization in the brain; different anatomical regions preferentially activate for certain types of visual input. For example, the f…
RIFF: Learning to Rephrase Inputs for Few-shot Fine-tuning of Language Models
Saeed Najafi, Alona Fyshe
Pre-trained Language Models (PLMs) can be accurately fine-tuned for downstream text processing tasks. Recently, researchers have introduced several parameter-efficient fine-tuning…
How to optimize neuroscience data utilization and experiment design for advancing brain models of visual and linguistic cognition?
Greta Tuckute, Dawn Finzi, Eshed Margalit +8
In recent years, neuroscience has made significant progress in building large-scale artificial neural network (ANN) models of brain activity and behavior. However, there is no cons…
Language and Mental Health: Measures of Emotion Dynamics from Text as Linguistic Biosocial Markers
Daniela Teodorescu, Tiffany Cheng, Alona Fyshe +1
Research in psychopathology has shown that, at an aggregate level, the patterns of emotional change over time -- emotion dynamics -- are indicators of one's mental health. One's pa…
Better Handling Coreference Resolution in Aspect Level Sentiment Classification by Fine-Tuning Language Models
Dhruv Mullick, Bilal Ghanem, Alona Fyshe
Customer feedback is invaluable to companies as they refine their products. Monitoring customer feedback can be automated with Aspect Level Sentiment Classification (ALSC) which al…
Utterance Emotion Dynamics in Children's Poems: Emotional Changes Across Age
Daniela Teodorescu, Alona Fyshe, Saif M. Mohammad
Emerging psychopathology studies are showing that patterns of changes in emotional state -- emotion dynamics -- are associated with overall well-being and mental health. More recen…
Identifying Shared Decodable Concepts in the Human Brain Using Image-Language Foundation Models
Cory Efird, Alex Murphy, Joel Zylberberg +1
We introduce a method that takes advantage of high-quality pretrained multimodal representations to explore fine-grained semantic networks in the human brain. Previous studies have…
DISTO: Evaluating Textual Distractors for Multi-Choice Questions using Negative Sampling based Approach
Bilal Ghanem, Alona Fyshe
Multiple choice questions (MCQs) are an efficient and common way to assess reading comprehension (RC). Every MCQ needs a set of distractor answers that are incorrect, but plausible…
Weakly-Supervised Questions for Zero-Shot Relation Extraction
Saeed Najafi, Alona Fyshe
Zero-Shot Relation Extraction (ZRE) is the task of Relation Extraction where the training and test sets have no shared relation types. This very challenging domain is a good test o…
Improving the Accuracy and Robustness of CNNs Using a Deep CCA Neural Data Regularizer
Cassidy Pirlot, Richard C. Gerum, Cory Efird +2
As convolutional neural networks (CNNs) become more accurate at object recognition, their representations become more similar to the primate visual system. This finding has inspire…
Different Spectral Representations in Optimized Artificial Neural Networks and Brains
Richard C. Gerum, Cassidy Pirlot, Alona Fyshe +1
Recent studies suggest that artificial neural networks (ANNs) that match the spectral properties of the mammalian visual cortex -- namely, the eigenspectrum of the covar…
Long Term Fairness for Minority Groups via Performative Distributionally Robust Optimization
Liam Peet-Pare, Nidhi Hegde, Alona Fyshe
Fairness researchers in machine learning (ML) have coalesced around several fairness criteria which provide formal definitions of what it means for an ML model to be fair. However,…
Discriminative Models Can Still Outperform Generative Models in Aspect Based Sentiment Analysis
Dhruv Mullick, Alona Fyshe, Bilal Ghanem
Aspect-based Sentiment Analysis (ABSA) helps to explain customers' opinions towards products and services. In the past, ABSA models were discriminative, but more recently generativ…
No More Pesky Hyperparameters: Offline Hyperparameter Tuning for RL
Han Wang, Archit Sakhadeo, Adam White +7
The performance of reinforcement learning (RL) agents is sensitive to the choice of hyperparameters. In real-world settings like robotics or industrial control systems, however, te…
Question Generation for Reading Comprehension Assessment by Modeling How and What to Ask
Bilal Ghanem, Lauren Lutz Coleman, Julia Rivard Dexter +2
Reading is integral to everyday life, and yet learning to read is a struggle for many young learners. During lessons, teachers can use comprehension questions to increase engagemen…
Resonance in Weight Space: Covariate Shift Can Drive Divergence of SGD with Momentum
Kirby Banman, Liam Peet-Pare, Nidhi Hegde +2
Most convergence guarantees for stochastic gradient descent with momentum (SGDm) rely on iid sampling. Yet, SGDm is often used outside this regime, in settings with temporally corr…
Predictive Representation Learning for Language Modeling
Qingfeng Lan, Luke Kumar, Martha White +1
To effectively perform the task of next-word prediction, long short-term memory networks (LSTMs) must keep track of many types of information. Some information is directly related…
From Language to Language-ish: How Brain-Like is an LSTM's Representation of Nonsensical Language Stimuli?
Maryam Hashemzadeh, Greta Kaufeld, Martha White +2
The representations generated by many models of language (word embeddings, recurrent neural networks and transformers) correlate to brain activity recorded while people read. Howev…