18 citations · 34 across the 11 of their papers we have counts for
12 papers
PLD+: Accelerating LLM inference by leveraging Language Model Artifacts
Shwetha Somasundaram, Anirudh Phukan, Apoorv Saxena
To reduce the latency associated with autoretrogressive LLM inference, speculative decoding has emerged as a novel decoding paradigm, where future tokens are drafted and verified i…
Beyond Logit Lens: Contextual Embeddings for Robust Hallucination Detection & Grounding in VLMs
Anirudh Phukan, Divyansh, Harshit Kumar Morj +3
The rapid development of Large Multimodal Models (LMMs) has significantly advanced multimodal understanding by harnessing the language abilities of Large Language Models (LLMs) and…
Enhancing Post-Hoc Attributions in Long Document Comprehension via Coarse Grained Answer Decomposition
Pritika Ramu, Koustava Goswami, Apoorv Saxena +1
Accurately attributing answer text to its source document is crucial for developing a reliable question-answering system. However, attribution for long documents remains largely un…
Enhancing Presentation Slide Generation by LLMs with a Multi-Staged End-to-End Approach
Sambaran Bandyopadhyay, Himanshu Maheshwari, Anandhavelu Natarajan +1
Generating presentation slides from a long document with multimodal elements such as text and images is an important task. This is time consuming and needs domain expertise if done…
Peering into the Mind of Language Models: An Approach for Attribution in Contextual Question Answering
Anirudh Phukan, Shwetha Somasundaram, Apoorv Saxena +2
With the enhancement in the field of generative artificial intelligence (AI), contextual question answering has become extremely relevant. Attributing model generations to the inpu…
Social Media Ready Caption Generation for Brands
Himanshu Maheshwari, Koustava Goswami, Apoorv Saxena +1
Social media advertisements are key for brand marketing, aiming to attract consumers with captivating captions and pictures or logos. While previous research has focused on generat…
Drilling Down into the Discourse Structure with LLMs for Long Document Question Answering
Inderjeet Nair, Shwetha Somasundaram, Apoorv Saxena +1
We address the task of evidence retrieval for long document question answering, which involves locating relevant paragraphs within a document to answer a question. We aim to assess…
A-STAR: Test-time Attention Segregation and Retention for Text-to-image Synthesis
Aishwarya Agarwal, Srikrishna Karanam, K J Joseph +3
While recent developments in text-to-image generative models have led to a suite of high-performing methods capable of producing creative imagery from free-form text, there are sev…
Friendly Neighbors: Contextualized Sequence-to-Sequence Link Prediction
Adrian Kochsiek, Apoorv Saxena, Inderjeet Nair +1
We propose KGT5-context, a simple sequence-to-sequence model for link prediction (LP) in knowledge graphs (KG). Our work expands on KGT5, a recent LP model that exploits textual fe…
TwiRGCN: Temporally Weighted Graph Convolution for Question Answering over Temporal Knowledge Graphs
Aditya Sharma, Apoorv Saxena, Chitrank Gupta +3
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 capabil…
Sequence-to-Sequence Knowledge Graph Completion and Question Answering
Apoorv Saxena, Adrian Kochsiek, Rainer Gemulla
Knowledge graph embedding (KGE) models represent each entity and relation of a knowledge graph (KG) with low-dimensional embedding vectors. These methods have recently been applied…
Question Answering Over Temporal Knowledge Graphs
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. While Question Answering over KG…