Icard, Thomas
9 papers on CoChat
Most cited papers
- Verified
On the Opportunities and Risks of Foundation Models
Bommasani, R., Hudson, D. A., Adeli, E., Altman, R., Arora, S., von Arx, S., Bernstein, M. S., Bohg, J., Bosselut, A., Brunskill, E., et al. (2021) · arXiv
Ethics and Social Impacts of AIArtificial Intelligence Applications
Cited by 2,676
- Verified
Holistic Evaluation of Language Models
Liang, P., Bommasani, R., Lee, T., Tsipras, D., Soylu, D., Yasunaga, M., Zhang, Y., Narayanan, D., Wu, Y., Kumar, A., et al. (2022) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 255
- Verified
On Pearl’s Hierarchy and the Foundations of Causal Inference
Bareinboim, E., Correa, J. D., Ibeling, D., & Icard, T. (2022) · Probabilistic and Causal Inference
Bayesian Modeling and Causal InferenceAdvanced Causal Inference Techniques
Cited by 174
- Verified
Normality and actual causal strength
Icard, T. F., Kominsky, J. F., & Knobe, J. (2017) · Cognition
Bayesian Modeling and Causal InferenceLogic, Reasoning, and Knowledge
Cited by 155
- Verified
Causal abstractions of neural networks
Geiger, A., Lu, H., Icard, T., & Potts, C. (2021) · arXiv
Explainable Artificial Intelligence (XAI)Bayesian Modeling and Causal Inference
Cited by 45
- Verified
Interpretability at Scale: Identifying Causal Mechanisms in Alpaca
Wu, Z., Geiger, A., Icard, T., Potts, C., & Goodman, N. D. (2023) · arXiv
Explainable Artificial Intelligence (XAI)Philosophy of Biology and Scientific Explanation
Cited by 14
- Verified
Causal Abstraction: A Theoretical Foundation for Mechanistic Interpretability
Geiger, A., Ibeling, D., Zur, A., Chaudhary, M., Chauhan, S., Huang, J., Arora, A., Wu, Z., Goodman, N., Potts, C., et al. (2023) · arXiv
Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques
Cited by 11
- Verified
A Topological Perspective on Causal Inference
Ibeling, D., & Icard, T. (2021) · arXiv
Bayesian Modeling and Causal InferencePhilosophy of Biology and Scientific Explanation
Cited by 4
- Verified
Belief in the Machine: Investigating Epistemological Blind Spots of Language Models
Suzgun, M., Gur, T., Bianchi, F., Ho, D. E., Icard, T., Jurafsky, D., & Zou, J. (2024) · arXiv
Logic, Reasoning, and KnowledgeTopic Modeling
Cited by 3
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