Ladhak, Faisal
14 papers on CoChatORCID 0009-0009-5730-3866
Most cited papers
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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
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Benchmarking Large Language Models for News Summarization
Zhang, T., Ladhak, F., Durmus, E., Liang, P., McKeown, K., & Hashimoto, T. B. (2023) · arXiv
Topic ModelingAdvanced Text Analysis Techniques
Cited by 415
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Benchmarking Large Language Models for News Summarization
Zhang, T., Ladhak, F., Durmus, E., Liang, P., McKeown, K., & Hashimoto, T. B. (2024) · Transactions of the Association for Computational Linguistics
Topic ModelingAdvanced Text Analysis Techniques
Cited by 415
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Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale
Bianchi, F., Kalluri, P., Durmus, E., Ladhak, F., Cheng, M., Nozza, D., Hashimoto, T., Jurafsky, D., Zou, J., & Caliskan, A. (2023) · 2023 ACM Conference on Fairness, Accountability, and Transparency
Ethics and Social Impacts of AIHate Speech and Cyberbullying Detection
Cited by 342
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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
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The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
Gehrmann, S., Adewumi, T., Aggarwal, K., Ammanamanchi, P. S., Aremu, A., Bosselut, A., Chandu, K. R., Clinciu, M.-A., Das, D., Dhole, K., et al. (2021) · Proceedings of the 1st Workshop on Natural Language Generation, Evaluation, and Metrics (GEM 2021)
Natural Language Processing TechniquesTopic Modeling
Cited by 159
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Whose Opinions Do Language Models Reflect?
Santurkar, S., Durmus, E., Ladhak, F., Lee, C., Liang, P., & Hashimoto, T. (2023) · arXiv
Sentiment Analysis and Opinion MiningEthics and Social Impacts of AI
Cited by 114
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Evaluating Human-Language Model Interaction
Lee, M., Srivastava, M., Hardy, A., Thickstun, J., Durmus, E., Paranjape, A., Gerard-Ursin, I., Li, X. L., Ladhak, F., Rong, F., et al. (2022) · arXiv
Speech and dialogue systemsNatural Language Processing Techniques
Cited by 61
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The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
Gehrmann, S., Adewumi, T., Aggarwal, K., Ammanamanchi, P. S., Anuoluwapo, A., Bosselut, A., Chandu, K. R., Clinciu, M., Das, D., Dhole, K. D., et al. (2021) · arXiv
Natural Language Processing TechniquesTopic Modeling
Cited by 49
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Faithful or Extractive? On Mitigating the Faithfulness-Abstractiveness Trade-off in Abstractive Summarization
Ladhak, F., Durmus, E., He, H., Cardie, C., & McKeown, K. (2022) · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Topic ModelingAdvanced Text Analysis Techniques
Cited by 46
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When Do Pre-Training Biases Propagate to Downstream Tasks? A Case Study in Text Summarization
Ladhak, F., Durmus, E., Suzgun, M., Zhang, T., Jurafsky, D., McKeown, K., & Hashimoto, T. (2023) · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
Topic ModelingNatural Language Processing Techniques
Cited by 30
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Spurious Correlations in Reference-Free Evaluation of Text Generation
Durmus, E., Ladhak, F., & Hashimoto, T. (2022) · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Natural Language Processing TechniquesTopic Modeling
Cited by 16
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Proving Test Set Contamination in Black Box Language Models
Oren, Y., Meister, N., Chatterji, N., Ladhak, F., & Hashimoto, T. B. (2023) · arXiv
Adversarial Robustness in Machine LearningTopic Modeling
Cited by 11
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L0-Reasoning Bench: Evaluating Procedural Correctness in Language Models via Simple Program Execution
Sun, S., Hsieh, C.-P., Ladhak, F., Arakelyan, E., Serano, S. A., & Ginsburg, B. (2025) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 0
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