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MAGNIFICO: Evaluating the In-Context Learning Ability of Large Language Models to Generalize to Novel Interpretations
MAGNIFICO: Evaluating the In-Context Learning Ability of Large Language Models to Generalize to Novel Interpretations
Humans possess a remarkable ability to assign novel interpretations to linguistic expressions, enabling them to learn new words and …
Conference on Empirical Methods in Natural Language Processing (EMNLP),  2023.
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TK-KNN: A Balanced Distance-Based Pseudo Labeling Approach for Semi-Supervised Intent Classification
TK-KNN: A Balanced Distance-Based Pseudo Labeling Approach for Semi-Supervised Intent Classification
The ability to detect intent in dialogue systems has become increasingly important in modern technology. These systems often generate a …
Conference on Empirical Methods in Natural Language Processing (EMNLP),  2023.
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Egocentric Planning for Scalable Embodied Task Achievement
Egocentric Planning for Scalable Embodied Task Achievement
Embodied agents face significant challenges when tasked with performing actions in diverse environments, particularly in generalizing …
Conference on Neural Information Processing Systems (NeurIPS),  2023.
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Equivariant Adaptation of Large Pre-Trained Models
Equivariant Adaptation of Large Pre-Trained Models
Equivariant networks are specifically designed to ensure consistent behavior with respect to a set of input transformations, leading to …
Conference on Neural Information Processing Systems (NeurIPS),  2023.
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Workflow discovery in low data regimes
Workflow discovery in low data regimes
Text-based dialogues are now widely used to solve real-world problems. In cases where solution strategies are already known, they can …
Workshop at the International Conference on Machine Learning (ICML),  2023.
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MAPL: Parameter-Efficient Adaptation of Unimodal Pre-Trained Models for Vision-Language Few-Shot Prompting
MAPL: Parameter-Efficient Adaptation of Unimodal Pre-Trained Models for Vision-Language Few-Shot Prompting
Large pre-trained models have proved to be remarkable zero- and (prompt-based) few-shot learners in unimodal vision and language tasks. …
European Chapter of the Association for Computational Linguistics (EACL),  2023.
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The StatCan Dialogue Dataset: Retrieving Data Tables through Conversations with Genuine Intents
The StatCan Dialogue Dataset: Retrieving Data Tables through Conversations with Genuine Intents
We introduce the StatCan Dialogue Dataset consisting of 4967 conversations between agents working at Statistics Canada and online users …
European Chapter of the Association for Computational Linguistics (EACL),  2023.
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Multilingual Code Retrieval Without Paired Data: A New Benchmark and Experiments
Multilingual Code Retrieval Without Paired Data: A New Benchmark and Experiments
We seek to overcome limitations to code retrieval quality posed by the scarcity of data containing pairs of code snippets and natural …
Workshop at the International Conference on Learning Representations (ICLR),  2023.
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Leveraging Human Preferences to Master Poetry
Leveraging Human Preferences to Master Poetry
Large language models have been fine-tuned to learn poetry via supervised learning on a dataset containing relevant examples. However, …
AAAI Workshops,  2023.
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Workflow discovery in low data regimes
Workflow discovery in low data regimes
Text-based dialogues are now widely used to solve real-world problems. In cases where solution strategies are already known, they can …
Transactions on Machine Learning Research,  2023.
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