Zobrazeno 1 - 10
of 27 486
pro vyhledávání: '"P Iyer"'
Autor:
Iyer, Sumun, Shinko, Forte
We show that for a countable discrete group which is locally of finite asymptotic dimension, the generic continuous action on Cantor space has hyperfinite orbit equivalence relation. In particular, this holds for free groups, answering a question of
Externí odkaz:
http://arxiv.org/abs/2409.03078
Autor:
Witherden, Freddie D., Vincent, Peter E., Trojak, Will, Abe, Yoshiaki, Akbarzadeh, Amir, Akkurt, Semih, Alhawwary, Mohammad, Caros, Lidia, Dzanic, Tarik, Giangaspero, Giorgio, Iyer, Arvind S., Jameson, Antony, Koch, Marius, Loppi, Niki, Mishra, Sambit, Modi, Rishit, Sáez-Mischlich, Gonzalo, Park, Jin Seok, Vermeire, Brian C., Wang, Lai
PyFR is an open-source cross-platform computational fluid dynamics framework based on the high-order Flux Reconstruction approach, specifically designed for undertaking high-accuracy scale-resolving simulations in the vicinity of complex engineering
Externí odkaz:
http://arxiv.org/abs/2408.16509
Machine Translation of Culture-Specific Items (CSIs) poses significant challenges. Recent work on CSI translation has shown some success using Large Language Models (LLMs) to adapt to different languages and cultures; however, a deeper analysis is ne
Externí odkaz:
http://arxiv.org/abs/2408.13534
Autor:
Sundaram, Jainaveen, Iyer, Ravi
Multimodal Large Language Models (MM-LLMs) have seen significant advancements in the last year, demonstrating impressive performance across tasks. However, to truly democratize AI, models must exhibit strong capabilities and be able to run efficientl
Externí odkaz:
http://arxiv.org/abs/2408.13402
Autor:
Iyer, Vivek, Malik, Bhavitvya, Stepachev, Pavel, Chen, Pinzhen, Haddow, Barry, Birch, Alexandra
Despite the recent popularity of Large Language Models (LLMs) in Machine Translation (MT), their performance in low-resource translation still lags significantly behind Neural Machine Translation (NMT) models. In this paper, we explore what it would
Externí odkaz:
http://arxiv.org/abs/2408.12780
Autor:
Iyer, Tejas
Consider a model where $N$ equal agents possess `values', belonging to $\mathbb{N}_0$, that are subject to incremental growth over time. More precisely, the values of the agents are represented by $N$ independent, increasing $\mathbb{N}_0$ valued pro
Externí odkaz:
http://arxiv.org/abs/2408.11516
Autor:
Giusto, Edoardo, Nuñez-Corrales, Santiago, Cao, Phuong, Cilardo, Alessandro, Iyer, Ravishankar K., Jiang, Weiwen, Rech, Paolo, Vella, Flavio, Montrucchio, Bartolomeo, Dasgupta, Samudra, Humble, Travis S.
Quantum Computing (QC) offers the potential to enhance traditional High-Performance Computing (HPC) workloads by leveraging the unique properties of quantum computers, leading to the emergence of a new paradigm: HPC-QC. While this integration present
Externí odkaz:
http://arxiv.org/abs/2408.10484
Regulatory compliance reporting in the pharmaceutical industry relies on detailed tables, but these are often under-utilized beyond compliance due to their unstructured format and arbitrary content. Extracting and semantically representing tabular da
Externí odkaz:
http://arxiv.org/abs/2408.09434
Autor:
Iyer, Kartheik G., Yunus, Mikaeel, O'Neill, Charles, Ye, Christine, Hyk, Alina, McCormick, Kiera, Ciuca, Ioana, Wu, John F., Accomazzi, Alberto, Astarita, Simone, Chakrabarty, Rishabh, Cranney, Jesse, Field, Anjalie, Ghosal, Tirthankar, Ginolfi, Michele, Huertas-Company, Marc, Jablonska, Maja, Kruk, Sandor, Liu, Huiling, Marchidan, Gabriel, Mistry, Rohit, Naiman, J. P., Peek, J. E. G., Polimera, Mugdha, Rodriguez, Sergio J., Schawinski, Kevin, Sharma, Sanjib, Smith, Michael J., Ting, Yuan-Sen, Walmsley, Mike
The exponential growth of astronomical literature poses significant challenges for researchers navigating and synthesizing general insights or even domain-specific knowledge. We present Pathfinder, a machine learning framework designed to enable lite
Externí odkaz:
http://arxiv.org/abs/2408.01556
Sparse autoencoders (SAEs) have shown promise in extracting interpretable features from complex neural networks. We present one of the first applications of SAEs to dense text embeddings from large language models, demonstrating their effectiveness i
Externí odkaz:
http://arxiv.org/abs/2408.00657