Zobrazeno 1 - 10
of 20 475
pro vyhledávání: '"A Raghav"'
Autor:
Ma, Liguo, Chaturvedi, Raghav, Nguyen, Phuong X., Watanabe, Kenji, Taniguchi, Takashi, Mak, Kin Fai, Shan, Jie
The realization of graphene has provided a bench-top laboratory for quantum electrodynamics. The low-energy excitations of graphene are two-dimensional massless Dirac fermions with opposite chiralities at the $\pm$K valleys of the graphene Brillouin
Externí odkaz:
http://arxiv.org/abs/2412.07150
Traditional greedy tokenization methods have been a critical step in Natural Language Processing (NLP), influencing how text is converted into tokens and directly impacting model performance. While subword tokenizers like Byte-Pair Encoding (BPE) are
Externí odkaz:
http://arxiv.org/abs/2412.06926
Autor:
Ramji, Raghav, Ramji, Keshav
Evaluating large language models (LLMs) on their linguistic reasoning capabilities is an important task to understand the gaps in their skills that may surface during large-scale adoption. In this work, we investigate the abilities of such models to
Externí odkaz:
http://arxiv.org/abs/2412.17819
In high energy physics, self-supervised learning (SSL) methods have the potential to aid in the creation of machine learning models without the need for labeled datasets for a variety of tasks, including those related to jets -- narrow sprays of part
Externí odkaz:
http://arxiv.org/abs/2412.05333
Autor:
Ponkshe, Kaustubh, Singhal, Raghav, Gorbunov, Eduard, Tumanov, Alexey, Horvath, Samuel, Vepakomma, Praneeth
Low-rank adapters have become a standard approach for efficiently fine-tuning large language models (LLMs), but they often fall short of achieving the performance of full fine-tuning. We propose a method, LoRA Silver Bullet or LoRA-SB, that approxima
Externí odkaz:
http://arxiv.org/abs/2411.19557
Measurements of jet substructure in ultra-relativistic heavy-ion collisions indicate that interactions with the quark-gluon plasma quench the jet showering process. Modern data-driven methods have shown promise in probing these modifications in the j
Externí odkaz:
http://arxiv.org/abs/2411.19389
The Needle-in-a-haystack (NIAH) test is a general task used to assess language models' (LMs') abilities to recall particular information from long input context. This framework however does not provide a means of analyzing what factors, beyond contex
Externí odkaz:
http://arxiv.org/abs/2411.19360
Autor:
Qureshi, Umar Sohail, Elayavalli, Raghav Kunnawalkam, Mozarsky, Luke, Caines, Helen, Mooney, Isaac
We present parameter sets corresponding to new underlying event tunes for the Herwig7.3 Monte Carlo event generator. The existing Herwig tunes are in good agreement with LHC data, however, they are not typically designed for center-of-mass energies b
Externí odkaz:
http://arxiv.org/abs/2411.16897
Autor:
Kapu, Nirmal Joshua, Karan, Raghav
This article surveys convolution-based models including convolutional neural networks (CNNs), Conformers, ResNets, and CRNNs-as speech signal processing models and provide their statistical backgrounds and speech recognition, speaker identification,
Externí odkaz:
http://arxiv.org/abs/2411.18636
Autor:
Gundavarapu, Nitesh Bharadwaj, Friedman, Luke, Goyal, Raghav, Hegde, Chaitra, Agustsson, Eirikur, Waghmare, Sagar M., Sirotenko, Mikhail, Yang, Ming-Hsuan, Weyand, Tobias, Gong, Boqing, Sigal, Leonid
Video understanding has witnessed significant progress with recent video foundation models demonstrating strong performance owing to self-supervised pre-training objectives; Masked Autoencoders (MAE) being the design of choice. Nevertheless, the majo
Externí odkaz:
http://arxiv.org/abs/2411.13683