Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Cardenas, Ronald"'
Preference Optimization (PO) has proven an effective step for aligning language models to human-desired behaviors. Current variants, following the offline Direct Preference Optimization objective, have focused on a strict setting where all tokens are
Externí odkaz:
http://arxiv.org/abs/2410.05102
Extractive summaries are usually presented as lists of sentences with no expected cohesion between them. In this paper, we aim to enforce cohesion whilst controlling for informativeness and redundancy in summaries, in cases where the input exhibits h
Externí odkaz:
http://arxiv.org/abs/2402.10643
Science journalism refers to the task of reporting technical findings of a scientific paper as a less technical news article to the general public audience. We aim to design an automated system to support this real-world task (i.e., automatic science
Externí odkaz:
http://arxiv.org/abs/2310.15077
Autor:
Gehrmann, Sebastian, Bhattacharjee, Abhik, Mahendiran, Abinaya, Wang, Alex, Papangelis, Alexandros, Madaan, Aman, McMillan-Major, Angelina, Shvets, Anna, Upadhyay, Ashish, Yao, Bingsheng, Wilie, Bryan, Bhagavatula, Chandra, You, Chaobin, Thomson, Craig, Garbacea, Cristina, Wang, Dakuo, Deutsch, Daniel, Xiong, Deyi, Jin, Di, Gkatzia, Dimitra, Radev, Dragomir, Clark, Elizabeth, Durmus, Esin, Ladhak, Faisal, Ginter, Filip, Winata, Genta Indra, Strobelt, Hendrik, Hayashi, Hiroaki, Novikova, Jekaterina, Kanerva, Jenna, Chim, Jenny, Zhou, Jiawei, Clive, Jordan, Maynez, Joshua, Sedoc, João, Juraska, Juraj, Dhole, Kaustubh, Chandu, Khyathi Raghavi, Perez-Beltrachini, Laura, Ribeiro, Leonardo F. R., Tunstall, Lewis, Zhang, Li, Pushkarna, Mahima, Creutz, Mathias, White, Michael, Kale, Mihir Sanjay, Eddine, Moussa Kamal, Daheim, Nico, Subramani, Nishant, Dusek, Ondrej, Liang, Paul Pu, Ammanamanchi, Pawan Sasanka, Zhu, Qi, Puduppully, Ratish, Kriz, Reno, Shahriyar, Rifat, Cardenas, Ronald, Mahamood, Saad, Osei, Salomey, Cahyawijaya, Samuel, Štajner, Sanja, Montella, Sebastien, Shailza, Jolly, Shailza, Mille, Simon, Hasan, Tahmid, Shen, Tianhao, Adewumi, Tosin, Raunak, Vikas, Raheja, Vipul, Nikolaev, Vitaly, Tsai, Vivian, Jernite, Yacine, Xu, Ying, Sang, Yisi, Liu, Yixin, Hou, Yufang
Evaluation in machine learning is usually informed by past choices, for example which datasets or metrics to use. This standardization enables the comparison on equal footing using leaderboards, but the evaluation choices become sub-optimal as better
Externí odkaz:
http://arxiv.org/abs/2206.11249
Publikováno v:
Journal of Artificial Intelligence Research, 80, 273-326 (2024)
Extractive summaries are usually presented as lists of sentences with no expected cohesion between them and with plenty of redundant information if not accounted for. In this paper, we investigate the trade-offs incurred when aiming to control for in
Externí odkaz:
http://arxiv.org/abs/2205.10192
Summarization systems face the core challenge of identifying and selecting important information. In this paper, we tackle the problem of content selection in unsupervised extractive summarization of long, structured documents. We introduce a wide ra
Externí odkaz:
http://arxiv.org/abs/2104.08392
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Akademický článek
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Unsupervised part of speech (POS) tagging is often framed as a clustering problem, but practical taggers need to \textit{ground} their clusters as well. Grounding generally requires reference labeled data, a luxury a low-resource language might not h
Externí odkaz:
http://arxiv.org/abs/1904.05426
Publikováno v:
Journal of Artificial Intelligence Research; 2024, Vol. 80, p273-326, 54p