Zobrazeno 1 - 10
of 302
pro vyhledávání: '"Nyberg, Eric"'
Autor:
Akter, Syeda Nahida, Prabhumoye, Shrimai, Kamalu, John, Satheesh, Sanjeev, Nyberg, Eric, Patwary, Mostofa, Shoeybi, Mohammad, Catanzaro, Bryan
The utility of synthetic data to enhance pretraining data quality and hence to improve downstream task accuracy has been widely explored in recent large language models (LLMs). Yet, these approaches fall inadequate in complex, multi-hop and mathemati
Externí odkaz:
http://arxiv.org/abs/2410.12881
Domain-specific question answering remains challenging for language models, given the deep technical knowledge required to answer questions correctly. This difficulty is amplified for smaller language models that cannot encode as much information in
Externí odkaz:
http://arxiv.org/abs/2408.10808
Autor:
Nyberg, Eric
Behovet av enklare bostadsbyggande är stort i Sverige. Det anses därför att en utveckling av samhällsbyggnadsprocessen måste ske. Siffror från Boverket visar på ett behov av att nästan 70 000 nya bostäder byggs varje år mellan 2024 och 2030
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-114565
Multimodal machine learning has gained significant attention in recent years due to its potential for integrating information from multiple modalities to enhance learning and decision-making processes. However, it is commonly observed that unimodal m
Externí odkaz:
http://arxiv.org/abs/2404.02359
Autor:
Yerramilli, Sahiti, Tamarapalli, Jayant Sravan, Kulkarni, Tanmay Girish, Francis, Jonathan, Nyberg, Eric
Deep Learning models are incredibly data-hungry and require very large labeled datasets for supervised learning. As a consequence, these models often suffer from overfitting, limiting their ability to generalize to real-world examples. Recent advance
Externí odkaz:
http://arxiv.org/abs/2404.02353
Verifying a question's validity before answering is crucial in real-world applications, where users may provide imperfect instructions. In this scenario, an ideal model should address the discrepancies in the query and convey them to the users rather
Externí odkaz:
http://arxiv.org/abs/2403.10534
The potential of Vision-Language Models (VLMs) often remains underutilized in handling complex text-based problems, particularly when these problems could benefit from visual representation. Resonating with humans' ability to solve complex text-based
Externí odkaz:
http://arxiv.org/abs/2401.08025
Autor:
Nyberg, Eric, Dinis Ferreira, Leandro
This paper will focus solely on the effectiveness of AV (antivirus) in detecting Metasploit payloads which have been encapsulated with different encapsulation modules. There seems to be a significant knowledge gap in the evaluation of commercial anti
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-122201
Autor:
Wilf, Alex, Akter, Syeda Nahida, Mathur, Leena, Liang, Paul Pu, Mathew, Sheryl, Shou, Mengrou, Nyberg, Eric, Morency, Louis-Philippe
The self-supervised objective of masking-and-predicting has led to promising performance gains on a variety of downstream tasks. However, while most approaches randomly mask tokens, there is strong intuition that deciding what to mask can substantial
Externí odkaz:
http://arxiv.org/abs/2305.14577
The retrieval model is an indispensable component for real-world knowledge-intensive tasks, e.g., open-domain question answering (ODQA). As separate retrieval skills are annotated for different datasets, recent work focuses on customized methods, lim
Externí odkaz:
http://arxiv.org/abs/2305.03130