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Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation
The practical utility of causality in decision-making is widely recognized, with causal discovery and inference being inherently …
Workshop on Structured Probabilistic Inference & Generative Modeling (ICML),  2023.
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Causal Discovery with Language Models as Imperfect Experts
Causal Discovery with Language Models as Imperfect Experts
Understanding the causal relationships that underlie a system is a fundamental prerequisite to accurate decision-making. In this work, …
Workshop on Structured Probabilistic Inference & Generative Modeling (ICML),  2023.
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Explaining Graph Neural Networks Using Interpretable Local Surrogates
Explaining Graph Neural Networks Using Interpretable Local Surrogates
We propose an interpretable local surrogate (ILS) method for understanding the predictions of black-box graph models. Explainability …
Workshop at the International Conference on Machine Learning (ICML),  2023.
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OC-NMN: Object-centric Compositional Neural Module Network for Generative Visual Analogical Reasoning
OC-NMN: Object-centric Compositional Neural Module Network for Generative Visual Analogical Reasoning
Imagination is a crucial aspect of human intelligence that enables us to combine concepts in novel ways and make sense of new …
Workshop at the International Conference on Machine Learning (ICML),  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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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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SantaCoder: don't reach for the stars!
SantaCoder: don't reach for the stars!
The BigCode project is an open-scientific collaboration working on the responsible development of large language models for code. This …
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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In-Context Learning for Text Classification with Many Labels
In-Context Learning for Text Classification with Many Labels
In-context learning (ICL) using large language models for tasks with many labels is challenging due to the limited context window, …
Workshop at the Conference on Empirical Methods in Natural Language Processing (EMNLP),  2022.
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On the Compositional Generalization Gap of In-Context Learning
On the Compositional Generalization Gap of In-Context Learning
Pretrained large generative language models have shown great performance on many tasks, but exhibit low compositional generalization …
Conference on Empirical Methods in Natural Language Processing (EMNLP),  2022.
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