Zobrazeno 1 - 10
of 1 384
pro vyhledávání: '"A, Siddartha."'
Autor:
Li, Boato, Weber, Tim, Kose, Umut, Franks, Matthew, Sgalaberna, Davide, Boyarintsev, Andrey, Sibilieva, Tetiana, Berns, Siddartha, Boillat, Eric, De Roeck, Albert, Dieminger, Till, Grynyov, Boris, Hugon, Sylvain, Jaeschke, Carsten, Rubbia, André
Plastic scintillators are widely used for the detection of elementary particles, and 3D reconstruction of particle tracks is achieved by segmenting the detector into 3D granular structures. In this study, we present a novel prototype fabricated by ad
Externí odkaz:
http://arxiv.org/abs/2412.10174
Autor:
Matta, Gopi Raju, Siddartha, Rahul, Girish, Rongali Simhachala Venkata, Sharma, Sumit, Mitra, Kaushik
Flare, an optical phenomenon resulting from unwanted scattering and reflections within a lens system, presents a significant challenge in imaging. The diverse patterns of flares, such as halos, streaks, color bleeding, and haze, complicate the flare
Externí odkaz:
http://arxiv.org/abs/2412.08200
Autor:
Purbey, Jebish, Sharma, Drishti, Gupta, Siddhant, Murad, Khawaja, Pullakhandam, Siddartha, Kadiyala, Ram Mohan Rao
This paper presents the system description of our entry for the COLING 2025 RegNLP RIRAG (Regulatory Information Retrieval and Answer Generation) challenge, focusing on leveraging advanced information retrieval and answer generation techniques in reg
Externí odkaz:
http://arxiv.org/abs/2412.06009
Autor:
Purbey, Jebish, Gupta, Siddhant, Manali, Nikhil, Pullakhandam, Siddartha, Sharma, Drishti, Srivastava, Ashay, Kadiyala, Ram Mohan Rao
This paper presents the system description of our entry for the COLING 2025 FMD challenge, focusing on misinformation detection in financial domains. We experimented with a combination of large language models, including Qwen, Mistral, and Gemma-2, a
Externí odkaz:
http://arxiv.org/abs/2412.00549
Autor:
Purbey, Jebish, Pullakhandam, Siddartha, Mehreen, Kanwal, Arham, Muhammad, Sharma, Drishti, Srivastava, Ashay, Kadiyala, Ram Mohan Rao
This paper presents a detailed system description of our entry for the CHiPSAL 2025 shared task, focusing on language detection, hate speech identification, and target detection in Devanagari script languages. We experimented with a combination of la
Externí odkaz:
http://arxiv.org/abs/2411.06850
Autor:
Kadiyala, Ram Mohan Rao, Pullakhandam, Siddartha, Mehreen, Kanwal, Tippareddy, Subhasya, Srivastava, Ashay
This paper presents our system description and error analysis of our entry for NLLP 2024 shared task on Legal Natural Language Inference (L-NLI) \citep{hagag2024legallenssharedtask2024}. The task required classifying these relationships as entailed,
Externí odkaz:
http://arxiv.org/abs/2410.15990
Autor:
Zhang, Yi, Chen, Zhen, Cheng, Chih-Hong, Ruan, Wenjie, Huang, Xiaowei, Zhao, Dezong, Flynn, David, Khastgir, Siddartha, Zhao, Xingyu
Text-to-Image (T2I) Diffusion Models (DMs) have garnered widespread attention for their impressive advancements in image generation. However, their growing popularity has raised ethical and social concerns related to key non-functional properties of
Externí odkaz:
http://arxiv.org/abs/2409.18214
Autor:
N, Siddartha Reddy, MV, Sai Prakash, V, Varun, Vaddina, Vishal, Gopalakrishnan, Saisubramaniam
Lead optimization is a pivotal task in the drug design phase within the drug discovery lifecycle. The primary objective is to refine the lead compound to meet specific molecular properties for progression to the subsequent phase of development. In th
Externí odkaz:
http://arxiv.org/abs/2407.13779
Autor:
White, Colin, Dooley, Samuel, Roberts, Manley, Pal, Arka, Feuer, Ben, Jain, Siddhartha, Shwartz-Ziv, Ravid, Jain, Neel, Saifullah, Khalid, Naidu, Siddartha, Hegde, Chinmay, LeCun, Yann, Goldstein, Tom, Neiswanger, Willie, Goldblum, Micah
Test set contamination, wherein test data from a benchmark ends up in a newer model's training set, is a well-documented obstacle for fair LLM evaluation and can quickly render benchmarks obsolete. To mitigate this, many recent benchmarks crowdsource
Externí odkaz:
http://arxiv.org/abs/2406.19314
Calibration is a well-studied property of predictors which guarantees meaningful uncertainty estimates. Multicalibration is a related notion -- originating in algorithmic fairness -- which requires predictors to be simultaneously calibrated over a po
Externí odkaz:
http://arxiv.org/abs/2406.06487