Search Results for author: Apoorv Saxena

Found 9 papers, 4 papers with code

Towards Optimizing the Costs of LLM Usage

no code implementations29 Jan 2024 Shivanshu Shekhar, Tanishq Dubey, Koyel Mukherjee, Apoorv Saxena, Atharv Tyagi, Nishanth Kotla

In this work, we propose optimizing the usage costs of LLMs by estimating their output quality (without actually invoking the LLMs), and then solving an optimization routine for the LLM selection to either keep costs under a budget, or minimize the costs, in a quality and latency aware manner.

Question Answering Sentence

Social Media Ready Caption Generation for Brands

no code implementations3 Jan 2024 Himanshu Maheshwari, Koustava Goswami, Apoorv Saxena, Balaji Vasan Srinivasan

Our architecture is based on two parts: a the first part contains an image captioning model that takes in an image that the brand wants to post online and gives a plain English caption; b the second part takes in the generated caption along with the target brand personality and outputs a catchy personality-aligned social media caption.

Image Captioning Marketing

Drilling Down into the Discourse Structure with LLMs for Long Document Question Answering

no code implementations22 Nov 2023 Inderjeet Nair, Shwetha Somasundaram, Apoorv Saxena, Koustava Goswami

We address the task of evidence retrieval for long document question answering, which involves locating relevant paragraphs within a document to answer a question.

Multi-hop Question Answering Question Answering +1

A-STAR: Test-time Attention Segregation and Retention for Text-to-image Synthesis

no code implementations ICCV 2023 Aishwarya Agarwal, Srikrishna Karanam, K J Joseph, Apoorv Saxena, Koustava Goswami, Balaji Vasan Srinivasan

First, our attention segregation loss reduces the cross-attention overlap between attention maps of different concepts in the text prompt, thereby reducing the confusion/conflict among various concepts and the eventual capture of all concepts in the generated output.

Denoising Image Generation +1

TwiRGCN: Temporally Weighted Graph Convolution for Question Answering over Temporal Knowledge Graphs

no code implementations12 Oct 2022 Aditya Sharma, Apoorv Saxena, Chitrank Gupta, Seyed Mehran Kazemi, Partha Talukdar, Soumen Chakrabarti

Recent years have witnessed much interest in temporal reasoning over knowledge graphs (KG) for complex question answering (QA), but there remains a substantial gap in human capabilities.

Knowledge Graphs Question Answering

Question Answering Over Temporal Knowledge Graphs

2 code implementations ACL 2021 Apoorv Saxena, Soumen Chakrabarti, Partha Talukdar

Temporal Knowledge Graphs (Temporal KGs) extend regular Knowledge Graphs by providing temporal scopes (start and end times) on each edge in the KG.

Knowledge Graphs Question Answering

Cannot find the paper you are looking for? You can Submit a new open access paper.