arXiv subjects

Saurabh Jain

Publications and source records attributed to Saurabh Jain.

6 recordsLinked to original sources

arXiv2026

AgentNLQ: A General-Purpose Agent for Natural Language to SQL

Natural language to SQL (NL2SQL) conversion is an important problem for researchers and enterprises due to the ubiquitous importance of relational databases in broad-ranging practical problems. Despite the rapid advancements in the capabilities of LLMs, NL2SQL has not reached parity in accuracy with human expert SQL writers, hence needing additional improvements in NL2SQL algorithms. This study presents a new multi-agent method for NL2SQL that achieves 78.1% semantic accuracy on the BIg Bench for LaRge-scale Database (BIRD) benchmark. Our method leverages a semantically enriched representation of user-provided schema, adds user-provided business rules, and produces accurate SQL queries. The main contributions of this study are (a) We designed an optimized new orchestrator in a multi-agent solution that uses LLMs to plan, orchestrate, reflect, and self-correct to generate accurate SQL queries, (b) We developed an advanced schema enrichment method that creates context-aware metadata to improve accuracy, and (c) We demonstrated the accuracy and generalizability of the method across different domains and datasets by evaluating it on the BIRD-SQL benchmark.

cs.AI↗

arXiv2024

Revolutionizing Modern Networks: Advances in AI, Machine Learning, and Blockchain for Quantum Satellites and UAV-based Communication

Quantum communication is the most secure technique of transmitting data available today. Fiber communication lines and satellite-to-ground links have served as the basis for the most successful quantum networks that have been developed so far. Using a UAV, satellite or both for free-space quantum communication reduces the need for permanent ground connections and takes advantage of the lower loss limit in space, which makes it more efficient. This work surveys the recent development in Quantum Satellites and Quantum UAVs-based networks. Here, the importance of the latest technologies, including quantum artificial intelligence, blockchain quantum machine learning, quantum satellites and quantum UAVs, are explored from network perspectives. Further, this work discussed the role of satellite-based images and artificial intelligence.

cs.NI↗

arXiv2024

RakutenAI-7B: Extending Large Language Models for Japanese

We introduce RakutenAI-7B, a suite of Japanese-oriented large language models that achieve the best performance on the Japanese LM Harness benchmarks among the open 7B models. Along with the foundation model, we release instruction- and chat-tuned models, RakutenAI-7B-instruct and RakutenAI-7B-chat respectively, under the Apache 2.0 license.

cs.CL↗

arXiv2022

Comparative Snippet Generation

We model product reviews to generate comparative responses consisting of positive and negative experiences regarding the product. Specifically, we generate a single-sentence, comparative response from a given positive and a negative opinion. We contribute the first dataset for this task of Comparative Snippet Generation from contrasting opinions regarding a product, and a performance analysis of a pre-trained BERT model to generate such snippets.

cs.CL↗

arXiv2021

MRCBert: A Machine Reading ComprehensionApproach for Unsupervised Summarization

When making an online purchase, it becomes important for the customer to read the product reviews carefully and make a decision based on that. However, reviews can be lengthy, may contain repeated, or sometimes irrelevant information that does not help in decision making. In this paper, we introduce MRCBert, a novel unsupervised method to generate summaries from product reviews. We leverage Machine Reading Comprehension, i.e. MRC, approach to extract relevant opinions and generate both rating-wise and aspect-wise summaries from reviews. Through MRCBert we show that we can obtain reasonable performance using existing models and transfer learning, which can be useful for learning under limited or low resource scenarios. We demonstrated our results on reviews of a product from the Electronics category in the Amazon Reviews dataset. Our approach is unsupervised as it does not require any domain-specific dataset, such as the product review dataset, for training or fine-tuning. Instead, we have used SQuAD v1.1 dataset only to fine-tune BERT for the MRC task. Since MRCBert does not require a task-specific dataset, it can be easily adapted and used in other domains.

cs.CL↗

arXiv2010

A Markov Chain Model for the Analysis of Round-Robin Scheduling Scheme

In the literature of Round-Robin scheduling scheme, each job is processed, one after the another after giving a fix quantum. In case of First-come first-served, each process is executed, if the previously arrived processed is completed. Both these scheduling schemes are used in this paper as its special cases. A Markov chain model is used to compare several scheduling schemes of the class. An index measure is defined to compare the model based efficiency of different scheduling schemes. One scheduling scheme which is the mixture of FIFO and round robin is found efficient in terms of model based study. The system simulation procedure is used to derive the conclusion of the content

cs.NI↗