1 code implementation • 28 Oct 2024 • Yilun Jin, Zheng Li, Chenwei Zhang, Tianyu Cao, Yifan Gao, Pratik Jayarao, Mao Li, Xin Liu, Ritesh Sarkhel, Xianfeng Tang, Haodong Wang, Zhengyang Wang, Wenju Xu, Jingfeng Yang, Qingyu Yin, Xian Li, Priyanka Nigam, Yi Xu, Kai Chen, Qiang Yang, Meng Jiang, Bing Yin
Shopping MMLU consists of 57 tasks covering 4 major shopping skills: concept understanding, knowledge reasoning, user behavior alignment, and multi-linguality, and can thus comprehensively evaluate the abilities of LLMs as general shop assistants.
no code implementations • 30 Mar 2024 • Ritesh Sarkhel, Xiaoqi Ren, Lauro Beltrao Costa, Guolong Su, Vincent Perot, Yanan Xie, Emmanouil Koukoumidis, Arnab Nandi
Pre-training an extractor model on unlabeled instances of the target document type, followed by a fine-tuning step on human-labeled instances does not work in these scenarios, as it surpasses the maximum allowable training time allocated for the extractor.
no code implementations • 1 Mar 2023 • Ritesh Sarkhel, Arnab Nandi
This makes it difficult to contextualize the information retrieved from querying these documents and gather actionable insights from them.
no code implementations • 27 Aug 2022 • Ritesh Sarkhel, Binxuan Huang, Colin Lockard, Prashant Shiralkar
Prior works rely on a few human-labeled web pages from each target website or thousands of human-labeled web pages from some seed websites to train a transferable extraction model that generalizes on unseen target websites.
no code implementations • 18 Aug 2020 • Bodhisatwa Mandal, Ritesh Sarkhel, Swarnendu Ghosh, Nibaran Das, Mita Nasipuri
To address this, we propose a novel two-phase dynamic routing protocol that computes agreements between neurons at various layers for micro and macro-level features, following a hierarchical learning paradigm.
1 code implementation • 27 Apr 2020 • Animesh Singh, Ritesh Sarkhel, Nibaran Das, Mahantapas Kundu, Mita Nasipuri
Finding local invariant patterns in handwrit-ten characters and/or digits for optical character recognition is a difficult task.
Optical Character Recognition
Optical Character Recognition (OCR)
no code implementations • COLING 2020 • Ritesh Sarkhel, Moniba Keymanesh, Arnab Nandi, Srinivasan Parthasarathy
Abstractive summarization at controllable lengths is a challenging task in natural language processing.
1 code implementation • 28 Dec 2019 • Animesh Singh, Sandip Saha, Ritesh Sarkhel, Mahantapas Kundu, Mita Nasipuri, Nibaran Das
Deep neural network-based architectures give promising results in various domains including pattern recognition.
no code implementations • 13 Jul 2019 • Bodhisatwa Mandal, Swarnendu Ghosh, Ritesh Sarkhel, Nibaran Das, Mita Nasipuri
Capsule networks have gained a lot of popularity in short time due to its unique approach to model equivariant class specific properties as capsules from images.
no code implementations • IEEE Applied Signal Processing Conference 2018 (ASPCON 2018) 2019 • Bodhisatwa Mandal, Suvam Dubey, Swarnendu Ghosh, Ritesh Sarkhel, Nibaran Das
Convolutional neural networks(CNNs) has become one of the primary algorithms for various computer vision tasks.
no code implementations • COLING 2018 • Promita Maitra, Ritesh Sarkhel
Using the encoding generated by Emoti-KATE, a 3-way classification is performed for every social media text in the dataset.
no code implementations • 14 Mar 2018 • Aritra Das, Swarnendu Ghosh, Ritesh Sarkhel, Sandipan Choudhuri, Nibaran Das, Mita Nasipuri
Modern deep learning algorithms have triggered various image segmentation approaches.
no code implementations • 2 May 2016 • Ritesh Sarkhel, Amit K Saha, Nibaran Das
A new region selection technique based on the idea of an enhanced Harmony Search methodology has been proposed here.