6 citations · 41 across the 26 of their papers we have counts for
14 papers · 1 filter
TextNCA: Neural Cellular Automata for Language Modeling via Hierarchical Local Attention
Avni Mittal, Avinash Anand, Ashutosh Kumar +7
Can a strictly local, iterated, weight-shared computation primitive support language modelling, and which of those three properties actually drives the model's behaviour? We define…
StocksTalk: A Voice-Enabled Conversational Agent for Structured Query Generation over Web Data
Akshat Parmar, Vikranth Udandarao, Abhay Shakya +4
StocksTalk is a voice-enabled conversational system for transforming spoken financial screening requests into executable and validated structured queries over real-world market dat…
The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes
Avinash Anand, Mahisha Ramesh, Avni Mittal +8
Reasoning has become central to how Large Language Models (LLMs) are evaluated and interpreted, spanning Chain-of-Thought (CoT), mathematical problem-solving, multi-hop question an…
Psychologically-Grounded Graph Modeling for Interpretable Depression Detection
Rishitej Reddy Vyalla, Kritarth Prasad, Avinash Anand +4
Automatic depression detection from conversational interactions holds significant promise for scalable screening but remains hindered by severe data scarcity and a lack of clinical…
IRIS: Interleaved Reinforcement with Incremental Staged Curriculum for Cross-Lingual Mathematical Reasoning
Navya Gupta, Rishitej Reddy Vyalla, Avinash Anand +8
Curriculum learning helps language models tackle complex reasoning by gradually increasing task difficulty. However, it often fails to generate consistent step-by-step reasoning, e…
Better and Worse with Scale: How Contextual Entrainment Diverges with Model Size
Dikshant Kukreja, Kshitij Sah, Gautam Gupta +5
Larger language models become simultaneously better and worse at handling contextual information -- better at ignoring false claims, worse at ignoring irrelevant tokens. We formali…
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…
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…
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…
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…
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…
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…
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…
Advancements in Scientific Controllable Text Generation Methods
Arnav Goel, Medha Hira, Avinash Anand +2
The previous work on controllable text generation is organized using a new schema we provide in this study. Seven components make up the schema, and each one is crucial to the crea…