Zobrazeno 1 - 10
of 2 396
pro vyhledávání: '"P. Vasudev"'
Autor:
Aflalo, Estelle, Stan, Gabriela Ben Melech, Le, Tiep, Luo, Man, Rosenman, Shachar, Paul, Sayak, Tseng, Shao-Yen, Lal, Vasudev
Large Vision Language Models (LVLMs) have achieved significant progress in integrating visual and textual inputs for multimodal reasoning. However, a recurring challenge is ensuring these models utilize visual information as effectively as linguistic
Externí odkaz:
http://arxiv.org/abs/2412.14672
We present a new approach to constructing and fitting dipoles and higher-order multipoles in synthetic galaxy samples over the sky. Within our Bayesian paradigm, we illustrate that this technique is robust to masked skies, allowing us to make credibl
Externí odkaz:
http://arxiv.org/abs/2412.12600
Are generative pre-trained transformer (GPT) models only trained to predict the next token, or do they implicitly learn a world model from which a sequence is generated one token at a time? We examine this question by deriving a causal interpretation
Externí odkaz:
http://arxiv.org/abs/2412.07446
Although capable of generating creative text, Large Language Models (LLMs) are poor judges of what constitutes "creativity". In this work, we show that we can leverage this knowledge of how to write creatively in order to better judge what is creativ
Externí odkaz:
http://arxiv.org/abs/2412.06060
Multimodal models typically combine a powerful large language model (LLM) with a vision encoder and are then trained on multimodal data via instruction tuning. While this process adapts LLMs to multimodal settings, it remains unclear whether this ada
Externí odkaz:
http://arxiv.org/abs/2412.03467
Autor:
Stan, Gabriela Ben-Melech, Aflalo, Estelle, Luo, Man, Rosenman, Shachar, Le, Tiep, Paul, Sayak, Tseng, Shao-Yen, Lal, Vasudev
While Large Vision Language Models (LVLMs) have become masterly capable in reasoning over human prompts and visual inputs, they are still prone to producing responses that contain misinformation. Identifying incorrect responses that are not grounded
Externí odkaz:
http://arxiv.org/abs/2412.01487
Autor:
Gohil, Vasudev, DeLorenzo, Matthew, Nallam, Veera Vishwa Achuta Sai Venkat, See, Joey, Rajendran, Jeyavijayan
The rapid advancement of large language models (LLMs) has enabled the ability to effectively analyze and generate code nearly instantaneously, resulting in their widespread adoption in software development. Following this advancement, researchers and
Externí odkaz:
http://arxiv.org/abs/2411.16111
Autor:
Glorioso, Paolo, Anthony, Quentin, Tokpanov, Yury, Golubeva, Anna, Shyam, Vasudev, Whittington, James, Pilault, Jonathan, Millidge, Beren
In this technical report, we present the Zamba2 series -- a suite of 1.2B, 2.7B, and 7.4B parameter hybrid Mamba2-transformer models that achieve state of the art performance against the leading open-weights models of their class, while achieving sub
Externí odkaz:
http://arxiv.org/abs/2411.15242
Autor:
Ratzlaff, Neale, Olson, Matthew Lyle, Hinck, Musashi, Aflalo, Estelle, Tseng, Shao-Yen, Lal, Vasudev, Howard, Phillip
Large Multi-Modal Models (LMMs) have demonstrated impressive capabilities as general-purpose chatbots that can engage in conversations about a provided input, such as an image. However, their responses are influenced by societal biases present in the
Externí odkaz:
http://arxiv.org/abs/2411.12590
Autor:
Notton, Cassandre, Sharma, Vasudev, Trinh, Vincent Quoc-Huy, Chen, Lina, Xu, Minqi, Varma, Sonal, Hosseini, Mahdi S.
Colorectal cancer (CRC) is one of the few cancers that have an established dysplasia-carcinoma sequence that benefits from screening. Everyone over 50 years of age in Canada is eligible for CRC screening. About 20\% of those people will undergo a bio
Externí odkaz:
http://arxiv.org/abs/2411.05959