1 citations · 1 across the 14 of their papers we have counts for
14 papers
Caching for the Future: Scrub Jay Episodic Memory Principles for Agent Memory Systems
Kartikey Singh Bhandari, Aarya Wadhwani, Dhruv Kumar +1
LLM agents that persist across sessions accumulate stored memories whose validity varies enormously by content type, yet existing memory architectures treat all memories as equally…
Trust Regions Sell, But Who's Buying? Overlap Geometry as an Alternative Trust Region for Policy Optimization
Gaurish Trivedi, Alakh Sharma, Kartikey Singh Bhandari +4
Standard trust-region methods constrain policy updates via Kullback-Leibler (KL) divergence. However, KL controls only an average divergence and does not directly prevent rare, lar…
Domain-Partitioned Hybrid RAG for Legal Reasoning: Toward Modular and Explainable Legal AI for India
Rakshita Goel, S Pranav Kumar, Anmol Agrawal +3
Legal research in India involves navigating long and heterogeneous documents spanning statutes, constitutional provisions, penal codes, and judicial precedents, where purely keywor…
A Hybrid Supervised-LLM Pipeline for Actionable Suggestion Mining in Unstructured Customer Reviews
Aakash Trivedi, Aniket Upadhyay, Pratik Narang +2
Extracting actionable suggestions from customer reviews is essential for operational decision-making, yet these directives are often embedded within mixed-intent, unstructured text…
Actionable Advice from Reviews via Mixture of LoRA Experts: A Two-LLM Pipeline for Issue Extraction and Business Recommendations
Kartikey Singh Bhandari, Manav Ganesh, Yashwant Viswanathan +3
Customer reviews contain detailed, domain specific signals about service failures and user expectations, but converting this unstructured feedback into actionable business decision…
Beyond Sentiment: A Multi-Agent Pipeline for Actionable Business Advice from Reviews
Kartikey Singh Bhandari, Tanish Jain, Archit Agrawal +3
Customer reviews contain valuable signals about service quality, but converting large-scale review corpora into actionable business recommendations remains difficult. Standard sent…
Understanding Virality: A Rubric based Vision-Language Model Framework for Short-Form Edutainment Evaluation
Arnav Gupta, Gurekas Singh Sahney, Hardik Rathi +4
Evaluating short-form video content requires moving beyond surface-level quality metrics toward human-aligned, multimodal reasoning. While existing frameworks like VideoScore-2 ass…
Investigating Spatial Attention Bias in Vision-Language Models
Aryan Chaudhary, Sanchit Goyal, Pratik Narang +1
Vision-Language Models have demonstrated remarkable capabilities in understanding visual content, yet systematic biases in their spatial processing remain largely unexplored. This…
Large Language Models as Pokémon Battle Agents: Strategic Play and Content Generation
Daksh Jain, Aarya Jain, Ashutosh Desai +4
Strategic decision-making in Pokémon battles presents a unique testbed for evaluating large language models. Pokémon battles demand reasoning about type matchups, statistical trade…
From Facts to Conclusions : Integrating Deductive Reasoning in Retrieval-Augmented LLMs
Shubham Mishra, Samyek Jain, Gorang Mehrishi +4
Retrieval-Augmented Generation (RAG) grounds large language models (LLMs) in external evidence, but fails when retrieved sources conflict or contain outdated or subjective informat…
Lights, Camera, Consistency: A Multistage Pipeline for Character-Stable AI Video Stories
Chayan Jain, Rishant Sharma, Archit Garg +3
Generating long, cohesive video stories with consistent characters is a significant challenge for current text-to-video AI. We introduce a method that approaches video generation i…
Navigating the Reality Gap: On-Device Continual Adaptation of ASR for Clinical Telephony
Darshil Chauhan, Adityasinh Solanki, Vansh Patel +5
Automatic Speech Recognition (ASR) can ease clinical documentation in resource-constrained regions, but deployment is hindered by a "Reality Gap" between laboratory performance and…
ReviewSense: Transforming Customer Review Dynamics into Actionable Business Insights
Siddhartha Krothapalli, Kartikey Singh Bhandari, Tridib Kumar Das +3
As customer feedback becomes increasingly central to strategic growth, the ability to derive actionable insights from unstructured reviews is essential. While traditional AI-driven…
Generative Evolutionary Meta-Solver (GEMS): Scalable Surrogate-Free Multi-Agent Reinforcement Learning
Alakh Sharma, Gaurish Trivedi, Kartikey Singh Bhandari +4
Scalable multi-agent reinforcement learning (MARL) remains a central challenge for AI. Existing population-based methods, like Policy-Space Response Oracles, PSRO, require storing…