2 citations · 3 across the 10 of their papers we have counts for
10 papers · 1 filter
JoinGR: Learning to Traverse Join Graphs for Table Retrieval
Sandipan De, Abhijit Chakraborty, Sambaran Bandyopadhyay +1
Retrieving the right tables is a prerequisite for Text-to-SQL over realistic databases. Dense table retrievers rank schema elements independently, but this ignores a key source of…
RSF-GLLM: Bridging the Semantic Gap in Multi-Hop Knowledge Graph QA via Recurrent Soft-Flow and Decoupled LLM Generation
Sambaran Bandyopadhyay, Ananth Muppidi
Multi-hop Question Answering over Knowledge Graphs faces a critical challenge: traditional retrieve-then-read pipelines break differentiability, preventing the retriever from learn…
Can LLMs Judge Better Than They Generate? Evaluating Task Asymmetry, Mechanistic Interpretability and Transferability for In-Context QA
Sambaran Bandyopadhyay
LLM-as-a-Judge and self-evaluation pipelines implicitly assume that evaluation is easier than generation. We test this in a controlled in-context QA setting where a context passage…
Towards AI-Assisted Research Writing: Benchmarking LLMs for AI/ML Introduction Generation
Krishna Garg, Firoz Shaik, Sambaran Bandyopadhyay +1
As researchers increasingly adopt LLMs as writing assistants, generating high-quality research paper introductions remains both challenging and essential. We introduce Scientific I…
Infogen: Generating Complex Statistical Infographics from Documents
Akash Ghosh, Aparna Garimella, Pritika Ramu +2
Statistical infographics are powerful tools that simplify complex data into visually engaging and easy-to-understand formats. Despite advancements in AI, particularly with LLMs, ex…
Leveraging Self-Attention for Input-Dependent Soft Prompting in LLMs
Ananth Muppidi, Abhilash Nandy, Sambaran Bandyopadhyay
The performance of large language models in domain-specific tasks necessitates fine-tuning, which is computationally expensive and technically challenging. This paper focuses on pa…
Taming LLMs with Negative Samples: A Reference-Free Framework to Evaluate Presentation Content with Actionable Feedback
Ananth Muppidi, Tarak Das, Sambaran Bandyopadhyay +2
The generation of presentation slides automatically is an important problem in the era of generative AI. This paper focuses on evaluating multimodal content in presentation slides…
Is This a Bad Table? A Closer Look at the Evaluation of Table Generation from Text
Pritika Ramu, Aparna Garimella, Sambaran Bandyopadhyay
Understanding whether a generated table is of good quality is important to be able to use it in creating or editing documents using automatic methods. In this work, we underline th…
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…
Presentations are not always linear! GNN meets LLM for Document-to-Presentation Transformation with Attribution
Himanshu Maheshwari, Sambaran Bandyopadhyay, Aparna Garimella +1
Automatically generating a presentation from the text of a long document is a challenging and useful problem. In contrast to a flat summary, a presentation needs to have a better a…