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Injection moulding is a well-established automated process for manufacturing a wide variety of plastic components in large volumes and with high precision. There are, however, process control challenges associated with each stage of injection mouldin
Externí odkaz:
http://arxiv.org/abs/2403.04388
Any social choice function (e.g the efficient allocation) can be implemented using different payment rules: first price, second price, all-pay, etc. All of these payment rules are guaranteed to have the same expected revenue by the revenue equivalenc
Externí odkaz:
http://arxiv.org/abs/2403.04856
We introduce Double Cost Volume Stereo Matching Network(DCVSMNet) which is a novel architecture characterised by by two small upper (group-wise) and lower (norm correlation) cost volumes. Each cost volume is processed separately, and a coupling modul
Externí odkaz:
http://arxiv.org/abs/2402.16473
Rapid progress in scalable, commoditized tools for data collection and data processing has made it possible for firms and policymakers to employ ever more complex metrics as guides for decision-making. These developments have highlighted a prevailing
Externí odkaz:
http://arxiv.org/abs/2402.14005
Autor:
Kariminejad, Mandana, Tormey, David, Ryan, Caitríona, O'Hara, Christopher, Weinert, Albert, McAfee, Marion
Minimising cycle time without inducing quality defects is a major challenge in the injection moulding (IM). Design of Experiment methods (DoE) have been widely studied for optimisation of the IM, however existing methods have limitations, including t
Externí odkaz:
http://arxiv.org/abs/2402.12077
Autor:
Wang, Boxin, Ping, Wei, McAfee, Lawrence, Xu, Peng, Li, Bo, Shoeybi, Mohammad, Catanzaro, Bryan
Pretraining auto-regressive large language models~(LLMs) with retrieval demonstrates better perplexity and factual accuracy by leveraging external databases. However, the size of existing pretrained retrieval-augmented LLM is still limited (e.g., Ret
Externí odkaz:
http://arxiv.org/abs/2310.07713
Autor:
Xu, Peng, Ping, Wei, Wu, Xianchao, McAfee, Lawrence, Zhu, Chen, Liu, Zihan, Subramanian, Sandeep, Bakhturina, Evelina, Shoeybi, Mohammad, Catanzaro, Bryan
Extending the context window of large language models (LLMs) is getting popular recently, while the solution of augmenting LLMs with retrieval has existed for years. The natural questions are: i) Retrieval-augmentation versus long context window, whi
Externí odkaz:
http://arxiv.org/abs/2310.03025
Publikováno v:
Functional Composite Materials, Vol 5, Iss 1, Pp 1-20 (2024)
Abstract In the production of polymeric drug delivery devices, dissolution profile and mechanical properties of the drug loaded polymeric matrix are considered important Critical Quality Attributes (CQA) for quality assurance. However, currently the
Externí odkaz:
https://doaj.org/article/42d7323e912443c3bb9aaf67b92377c5
Autor:
Broder, Andrei Z., McAfee, Preston
We present a new framework to conceptualize and operationalize the total user experience of search, by studying the entirety of a search journey from an utilitarian point of view. Web search engines are widely perceived as "free". But search requires
Externí odkaz:
http://arxiv.org/abs/2308.07525
Autor:
Wang, Boxin, Ping, Wei, Xu, Peng, McAfee, Lawrence, Liu, Zihan, Shoeybi, Mohammad, Dong, Yi, Kuchaiev, Oleksii, Li, Bo, Xiao, Chaowei, Anandkumar, Anima, Catanzaro, Bryan
Large decoder-only language models (LMs) can be largely improved in terms of perplexity by retrieval (e.g., RETRO), but its impact on text generation quality and downstream task accuracy is unclear. Thus, it is still an open question: shall we pretra
Externí odkaz:
http://arxiv.org/abs/2304.06762