7 citations · 20 across the 16 of their papers we have counts for
16 papers
SpatialMath: Spatial Comprehension-Infused Symbolic Reasoning for Mathematical Problem-Solving
Ashutosh Bajpai, Akshat Bhandari, Akshay Nambi +1
Multimodal Small-to-Medium sized Language Models (MSLMs) have demonstrated strong capabilities in integrating visual and textual information but still face significant limitations…
Exposing Weak Links in Multi-Agent Systems under Adversarial Prompting
Nirmit Arora, Sathvik Joel, Ishan Kavathekar +6
LLM-based agents are increasingly deployed in multi-agent systems (MAS). As these systems move toward real-world applications, their security becomes paramount. Existing research l…
Think Right: Learning to Mitigate Under-Over Thinking via Adaptive, Attentive Compression
Joykirat Singh, Justin Chih-Yao Chen, Archiki Prasad +3
Recent thinking models are capable of solving complex reasoning tasks by scaling test-time compute, but this scaling should be allocated in line with task difficulty. On one hand,…
GeoBS: Information-Theoretic Quantification of Geographic Bias in AI Models
Zhangyu Wang, Nemin Wu, Qian Cao +8
The widespread adoption of AI models, especially foundation models (FMs), has made a profound impact on numerous domains. However, it also raises significant ethical concerns, incl…
Shiksha Copilot: Teacher-AI Collaboration for Curating and Customizing Lesson Plans in Low-Resource Schools
Deepak Varuvel Dennison, Bakhtawar Ahtisham, Kavyansh Chourasia +6
This study investigates Shiksha copilot, an AI-assisted lesson planning tool deployed in government schools across Karnataka, India. The system combined LLMs and human expertise th…
Agentic Reasoning and Tool Integration for LLMs via Reinforcement Learning
Joykirat Singh, Raghav Magazine, Yash Pandya +1
Large language models (LLMs) have achieved remarkable progress in complex reasoning tasks, yet they remain fundamentally limited by their reliance on static internal knowledge and…
eARCO: Efficient Automated Root Cause Analysis with Prompt Optimization
Drishti Goel, Raghav Magazine, Supriyo Ghosh +5
Root cause analysis (RCA) for incidents in large-scale cloud systems is a complex, knowledge-intensive task that often requires significant manual effort from on-call engineers (OC…
EnCortex: A General, Extensible and Scalable Framework for Decision Management in New-age Energy Systems
Millend Roy, Vaibhav Balloli, Anupam Sobti +4
With increased global warming, there has been a significant emphasis to replace fossil fuel-dependent energy sources with clean, renewable sources. These new-age energy systems are…
Self-Evolved Preference Optimization for Enhancing Mathematical Reasoning in Small Language Models
Joykirat Singh, Tanmoy Chakraborty, Akshay Nambi
Large language models (LLMs) have significantly improved their reasoning capabilities; however, they still struggle with complex multi-step mathematical problem-solving due to erro…
Exposing the Achilles' Heel: Evaluating LLMs Ability to Handle Mistakes in Mathematical Reasoning
Joykirat Singh, Akshay Nambi, Vibhav Vineet
Large Language Models (LLMs) have been applied to Math Word Problems (MWPs) with transformative impacts, revolutionizing how these complex problems are approached and solved in var…
TorchSpatial: A Location Encoding Framework and Benchmark for Spatial Representation Learning
Nemin Wu, Qian Cao, Zhangyu Wang +12
Spatial representation learning (SRL) aims at learning general-purpose neural network representations from various types of spatial data (e.g., points, polylines, polygons, network…
Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal Large Language Models
Hengyi Wang, Haizhou Shi, Shiwei Tan +6
Multimodal Large Language Models (MLLMs) have shown significant promise in various applications, leading to broad interest from researchers and practitioners alike. However, a comp…
MMCTAgent: Multi-modal Critical Thinking Agent Framework for Complex Visual Reasoning
Somnath Kumar, Yash Gadhia, Tanuja Ganu +1
Recent advancements in Multi-modal Large Language Models (MLLMs) have significantly improved their performance in tasks combining vision and language. However, challenges persist i…
PromptWizard: Task-Aware Prompt Optimization Framework
Eshaan Agarwal, Joykirat Singh, Vivek Dani +3
Large language models (LLMs) have transformed AI across diverse domains, with prompting being central to their success in guiding model outputs. However, manual prompt engineering…
Bridging the Language Gap: Dynamic Learning Strategies for Improving Multilingual Performance in LLMs
Somnath Kumar, Vaibhav Balloli, Mercy Ranjit +5
Large language models (LLMs) have revolutionized various domains but still struggle with non-Latin scripts and low-resource languages. This paper addresses the critical challenge o…
Chanakya: Learning Runtime Decisions for Adaptive Real-Time Perception
Anurag Ghosh, Vaibhav Balloli, Akshay Nambi +2
Real-time perception requires planned resource utilization. Computational planning in real-time perception is governed by two considerations -- accuracy and latency. There exist ru…