6 citations · 41 across the 26 of their papers we have counts for
30 papers
dKFD: Phase-Structured Evidence Allocation for Fixed-Budget Localized Event Understanding
Aditya Bagri, Ashutosh Kumar, Chaitanya Lakhchaura +3
Sparse video understanding often requires selecting a small set of visual evidence under a fixed frame budget. Most sparse selectors allocate this budget globally, allowing all fra…
NutriVision: Ingredient-Conditioned Fusion and Prediction for Single-Image Food Nutrition Estimation
Aman Kumar, Avinash Anand, Chaitanya Lakhchaura +5
Nutrition estimation is a fundamental task in consumer diet tracking, clinical dietetics, chronic disease management, sports and hospital nutrition, and broader food computing syst…
SynDORBench: Evaluating LVLM Perceptual Robustness Under Physically Constrained Visibility Conditions
Jeremy Stephen Gabriel Yee, Zhengkui Wang, Zhiyuan Zhang +5
Large vision-language models (LVLMs) have demonstrated remarkable performance on multimodal reasoning benchmarks, yet their perceptual reliability under physically constrained imag…
How Do VLMs Fail? Vision-Operation Misalignment in Compositional VQA
Navya Gupta, Bingjie Xu, Avinash Anand +2
Compositional visual question answering requires Vision-Language Models (VLMs) to execute multiple reasoning operations like object selection, spatial relation resolution, and attr…
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…
FORGE: Fused On-Register Gradient Elimination for Memory-Efficient LLM Training
Dikshant Kukreja, Kritarth Prasad, Avinash Anand +6
Reverse-mode differentiation computes every weight gradient, writes it to memory, and only then lets the optimizer read it back. This two-phase schedule sets the memory ceiling of…
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…
Enhancing Scientific Visual Question Answering via Vision-Caption aware Supervised Fine-Tuning
Janak Kapuriya, Anwar Shaikh, Arnav Goel +8
In this study, we introduce Vision-Caption aware Supervised FineTuning (VCASFT), a novel learning paradigm designed to enhance the performance of smaller Vision Language Models(VLM…
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…
Su-RoBERTa: A Semi-supervised Approach to Predicting Suicide Risk through Social Media using Base Language Models
Chayan Tank, Shaina Mehta, Sarthak Pol +4
In recent times, more and more people are posting about their mental states across various social media platforms. Leveraging this data, AI-based systems can be developed that help…
Enhancing LLMs for Physics Problem-Solving using Reinforcement Learning with Human-AI Feedback
Avinash Anand, Kritarth Prasad, Chhavi Kirtani +6
Large Language Models (LLMs) have demonstrated strong capabilities in text-based tasks but struggle with the complex reasoning required for physics problems, particularly in advanc…
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…
Improving Multimodal LLMs Ability In Geometry Problem Solving, Reasoning, And Multistep Scoring
Avinash Anand, Raj Jaiswal, Abhishek Dharmadhikari +6
This paper presents GPSM4K, a comprehensive geometry multimodal dataset tailored to augment the problem-solving capabilities of Large Vision Language Models (LVLMs). GPSM4K encompa…
Improving Physics Reasoning in Large Language Models Using Mixture of Refinement Agents
Raj Jaiswal, Dhruv Jain, Harsh Parimal Popat +4
Large Language Models (LLMs) demonstrate remarkable capabilities in various reasoning tasks. However, they encounter significant challenges when it comes to scientific reasoning, p…
A Comprehensive Survey of AI-Driven Advancements and Techniques in Automated Program Repair and Code Generation
Avinash Anand, Akshit Gupta, Nishchay Yadav +1
Bug fixing and code generation have been core research topics in software development for many years. The recent explosive growth in Large Language Models has completely transforme…
Depression Detection and Analysis using Large Language Models on Textual and Audio-Visual Modalities
Chayan Tank, Sarthak Pol, Vinayak Katoch +3
Depression has proven to be a significant public health issue, profoundly affecting the psychological well-being of individuals. If it remains undiagnosed, depression can lead to s…
Keystroke Dynamics Against Academic Dishonesty in the Age of LLMs
Debnath Kundu, Atharva Mehta, Rajesh Kumar +4
The transition to online examinations and assignments raises significant concerns about academic integrity. Traditional plagiarism detection systems often struggle to identify inst…
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…