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20232026
most citedContext-Enhanced Language Models for Generating Multi-Paper Citations

6 citations · 41 across the 26 of their papers we have counts for

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Showing 2024 · cs.CLShow all

7 papers · 2 filters

cs.CL2024

Multilingual Mathematical Reasoning: Advancing Open-Source LLMs in Hindi and English

Avinash Anand, Kritarth Prasad, Chhavi Kirtani +4

Large Language Models (LLMs) excel in linguistic tasks but struggle with mathematical reasoning, particularly in non English languages like Hindi. This research aims to enhance the…

cs.CL2024★ 2 cited

Knowledge Graphs are all you need: Leveraging KGs in Physics Question Answering

Krishnasai Addala, Kabir Dev Paul Baghel, Dhruv Jain +5

This study explores the effectiveness of using knowledge graphs generated by large language models to decompose high school-level physics questions into sub-questions. We introduce…

cs.CL2024

Steps are all you need: Rethinking STEM Education with Prompt Engineering

Krishnasai Addala, Kabir Dev Paul Baghel, Navya Gupta +4

Few shot and Chain-of-Thought prompting have shown promise when applied to Physics Question Answering Tasks, but are limited by the lack of mathematical ability inherent to LLMs, a…

cs.CL2024★ 6 cited

Context-Enhanced Language Models for Generating Multi-Paper Citations

Avinash Anand, Kritarth Prasad, Ujjwal Goel +4

Citation text plays a pivotal role in elucidating the connection between scientific documents, demanding an in-depth comprehension of the cited paper. Constructing citations is oft…

cs.CL2024★ 5 cited

Mathify: Evaluating Large Language Models on Mathematical Problem Solving Tasks

Avinash Anand, Mohit Gupta, Kritarth Prasad +5

The rapid progress in the field of natural language processing (NLP) systems and the expansion of large language models (LLMs) have opened up numerous opportunities in the field of…

cs.CL2024

KG-CTG: Citation Generation through Knowledge Graph-guided Large Language Models

Avinash Anand, Mohit Gupta, Kritarth Prasad +4

Citation Text Generation (CTG) is a task in natural language processing (NLP) that aims to produce text that accurately cites or references a cited document within a source documen…

cs.CL2024★ 2 cited

MM-PhyQA: Multimodal Physics Question-Answering With Multi-Image CoT Prompting

Avinash Anand, Janak Kapuriya, Apoorv Singh +5

While Large Language Models (LLMs) can achieve human-level performance in various tasks, they continue to face challenges when it comes to effectively tackling multi-step physics r…