Zobrazeno 1 - 10
of 1 793
pro vyhledávání: '"P, Aswathy"'
Autor:
Khan, Arham, Underwood, Robert, Siebenschuh, Carlo, Babuji, Yadu, Ajith, Aswathy, Hippe, Kyle, Gokdemir, Ozan, Brace, Alexander, Chard, Kyle, Foster, Ian
Deduplication is a major focus for assembling and curating training datasets for large language models (LLM) -- detecting and eliminating additional instances of the same content -- in large collections of technical documents. Unrestrained, duplicate
Externí odkaz:
http://arxiv.org/abs/2411.04257
Autor:
Khan, Arham, Nief, Todd, Hudson, Nathaniel, Sakarvadia, Mansi, Grzenda, Daniel, Ajith, Aswathy, Pettyjohn, Jordan, Chard, Kyle, Foster, Ian
Understanding neural networks is crucial to creating reliable and trustworthy deep learning models. Most contemporary research in interpretability analyzes just one model at a time via causal intervention or activation analysis. Yet despite successes
Externí odkaz:
http://arxiv.org/abs/2410.12927
Autor:
Schäfer, Johannes, Combs, Aidan, Bagdon, Christopher, Li, Jiahui, Probol, Nadine, Greschner, Lynn, Papay, Sean, Resendiz, Yarik Menchaca, Velutharambath, Aswathy, Wührl, Amelie, Weber, Sabine, Klinger, Roman
Demographics and cultural background of annotators influence the labels they assign in text annotation -- for instance, an elderly woman might find it offensive to read a message addressed to a "bro", but a male teenager might find it appropriate. It
Externí odkaz:
http://arxiv.org/abs/2410.08820
Autor:
Sakarvadia, Mansi, Ajith, Aswathy, Khan, Arham, Hudson, Nathaniel, Geniesse, Caleb, Chard, Kyle, Yang, Yaoqing, Foster, Ian, Mahoney, Michael W.
Language models (LMs) can "memorize" information, i.e., encode training data in their weights in such a way that inference-time queries can lead to verbatim regurgitation of that data. This ability to extract training data can be problematic, for exa
Externí odkaz:
http://arxiv.org/abs/2410.02159
The statement "The earth is flat" is factually inaccurate, but if someone truly believes and argues in its favor, it is not deceptive. Research on deception detection and fact checking often conflates factual accuracy with the truthfulness of stateme
Externí odkaz:
http://arxiv.org/abs/2409.20165
Long-range multi-particle correlations in heavy-ion collisions have shown conclusive evidence of the hydrodynamic behavior of strongly interacting matter, and are associated with the final-state azimuthal momentum anisotropy. In small collision syste
Externí odkaz:
http://arxiv.org/abs/2407.03823
Autor:
Wan, Yuwei, Liu, Yixuan, Ajith, Aswathy, Grazian, Clara, Hoex, Bram, Zhang, Wenjie, Kit, Chunyu, Xie, Tong, Foster, Ian
We introduce SciQAG, a novel framework for automatically generating high-quality science question-answer pairs from a large corpus of scientific literature based on large language models (LLMs). SciQAG consists of a QA generator and a QA evaluator, w
Externí odkaz:
http://arxiv.org/abs/2405.09939
If a person firmly believes in a non-factual statement, such as "The Earth is flat", and argues in its favor, there is no inherent intention to deceive. As the argumentation stems from genuine belief, it may be unlikely to exhibit the linguistic prop
Externí odkaz:
http://arxiv.org/abs/2403.10185
Autor:
Aswathy, M. S., Rosti, Marco E
This study explores the dynamics of finite-size fibers suspended freely in a viscoelastic turbulent flow. For a fiber suspended in Newtonian flows, two different flapping regimes were identified previously by Rosti et al (2018). Here we explore, how
Externí odkaz:
http://arxiv.org/abs/2403.04305
Autor:
Sakarvadia, Mansi, Khan, Arham, Ajith, Aswathy, Grzenda, Daniel, Hudson, Nathaniel, Bauer, André, Chard, Kyle, Foster, Ian
Transformer-based Large Language Models (LLMs) are the state-of-the-art for natural language tasks. Recent work has attempted to decode, by reverse engineering the role of linear layers, the internal mechanisms by which LLMs arrive at their final pre
Externí odkaz:
http://arxiv.org/abs/2310.16270