Measuring and Improving Persuasiveness of Large Language Models
LLMs are increasingly being used in workflows involving generating content to be consumed by humans (e.g., marketing) and also in …
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Measuring and Improving Persuasiveness of Large Language Models
It Helps to Take a Second Opinion: Teaching Smaller LLMs To Deliberate Mutually via Selective Rationale Optimisation
Very large language models (LLMs) such as GPT-4 have shown the ability to handle complex tasks by generating and self-refining …
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It Helps to Take a Second Opinion: Teaching Smaller LLMs To Deliberate Mutually via Selective Rationale Optimisation
Measuring And Improving Engagement of Text-to-Image Generation Models
Recent advances in text-to-image generation have achieved impressive aesthetic quality, making these models usable for both personal …
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Measuring And Improving Engagement of Text-to-Image Generation Models
AdQuestA: Knowledge-Guided Visual Question Answer Framework For Advertisements
In the rapidly evolving landscape of digital marketing, effective customer engagement through advertisements is crucial for brands. …
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Long-Term Ad Memorability: Understanding & Generating Memorable Ads
Despite the importance of long-term memory in marketing and brand building, until now, there has been no large-scale study on the …
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Long-Term Ad Memorability: Understanding & Generating Memorable Ads
ReEdit: Multimodal Exemplar-Based Image Editing using Diffusion Models
Modern Text-to-Image (T2I) Diffusion models have revolutionized image editing by enabling the generation of high-quality photorealistic …
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POSIX: Prompt Sensitivity Index for Large Language Models
Despite their remarkable capabilities, Large Language Models (LLMs) are found to be surprisingly sensitive to minor variations in …
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SMART: Submodular Data Mixture Strategy for Instruction Tuning
Instruction Tuning involves finetuning a language model on a collection of instruction-formatted datasets in order to enhance the …
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CABINET: Content Relevance based Noise Reduction for Table Question Answering
Table understanding capability of Large Language Models (LLMs) has been extensively studied through the task of question-answering (QA) …
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CABINET: Content Relevance based Noise Reduction for Table Question Answering
Advances in Citation Text Generation: Leveraging Multi-Source Seq2Seq Models and Large Language Models
Citation Text Generation (CTG) in scientific documents often relies on standard summarization techniques, which may not fully capture …
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