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While large language models have shown impressive capabilities across a wide range of domains, they still encounter significant challenges in reasoning tasks that require gathering evidence over multiple turns and drawing logical conclusions. These c
Externí odkaz:
http://arxiv.org/abs/2410.10998
One of the major drawbacks of deep learning models for computer vision has been their inability to retain multiple sources of information in a modular fashion. For instance, given a network that has been trained on a source task, we would like to re-
Externí odkaz:
http://arxiv.org/abs/2308.13957
Oftentimes, environments for sequential decision-making problems can be quite sparse in the provision of evaluative feedback to guide reinforcement-learning agents. In the extreme case, long trajectories of behavior are merely punctuated with a singl
Externí odkaz:
http://arxiv.org/abs/2307.11897
Autor:
Kansky, Ken, Vaidyanath, Skanda, Swingle, Scott, Lou, Xinghua, Lazaro-Gredilla, Miguel, George, Dileep
While recent advances in artificial intelligence have achieved human-level performance in environments like Starcraft and Go, many physical reasoning tasks remain challenging for modern algorithms. To date, few algorithms have been evaluated on physi
Externí odkaz:
http://arxiv.org/abs/2301.10289
Publikováno v:
Archives of Mental Health, Vol 25, Iss 1, Pp 51-56 (2024)
Context: Psychosocial dysfunction is the dysfunction in the various psychosocial areas, such as personal, vocational/occupational, familial, and social, which ultimately depends on the cognitive functioning of an individual. Any disturbances and fail
Externí odkaz:
https://doaj.org/article/10f7b562aac9432da0149855ae266d00
Learning policies that effectively utilize language instructions in complex, multi-task environments is an important problem in sequential decision-making. While it is possible to condition on the entire language instruction directly, such an approac
Externí odkaz:
http://arxiv.org/abs/2203.00054
Autor:
Jain, Naman, Vaidyanath, Skanda, Iyer, Arun, Natarajan, Nagarajan, Parthasarathy, Suresh, Rajamani, Sriram, Sharma, Rahul
Large pre-trained language models such as GPT-3, Codex, and Google's language model are now capable of generating code from natural language specifications of programmer intent. We view these developments with a mixture of optimism and caution. On th
Externí odkaz:
http://arxiv.org/abs/2112.02969
Publikováno v:
CoDAS, Vol 36, Iss 1 (2023)
ABSTRACT Purpose The purpose of the study was to develop the Tamil Matrix Sentence Test (TMST) and evaluate the performance of a group of young adults with normal hearing on the developed test. The developed sentences were also administered at varyin
Externí odkaz:
https://doaj.org/article/e1bb6d0c0e4e4cf18acf8cc713a844a9
Publikováno v:
Frontiers in Computer Science, Vol 5 (2023)
IntroductionThe contribution of technology to the field of health is vast, both in diagnosis and management. More so, the use of computer-based intervention has become increasingly widespread over the past decade. Human beings experience a decline in
Externí odkaz:
https://doaj.org/article/5da8d54efaef4e42becfd9179a716413
Autor:
Ramya Sudersonam, Ramya Vaidyanath
Publikováno v:
Auditory and Vestibular Research, Vol 32, Iss 2 (2023)
Background and Aim: Dichotic listening has been defined as the simultaneous stimulation of both ears and has been used to evaluate a listener’s binaural integration/separation ability. Dichotic tests are available in various languages and use varie
Externí odkaz:
https://doaj.org/article/6fc78574e63946b7840f0c9497cf0a21