Author: Janhavi Lande

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Janhavi Lande, is an Engineering Physics graduate from IIT Guwahati, class of 2023. She is an upcoming data scientist and has been working in the world of ml/ai research for the past two years. She is most fascinated by this ever changing world and its constant demand of humans to keep up with it. In her pastime she enjoys traveling, reading and writing poems.

This AI Research Presents Neural A*: A Novel Data-Driven Search Method for Path Planning Problems

AI Shorts
Path planning identifies a cost-effective and valid path from an initial point to a target point within an environmental map. Search-based planning methods, which...

CMU & Google DeepMind Researchers Introduce AlignProp: A Direct Backpropagation-Based AI Approach to Finetune Text-to-Image Diffusion Models for Desired Reward Function

AI Shorts
Probabilistic diffusion models have become the established norm for generative modeling in continuous domains. Leading the way in text-to-image diffusion models is DALLE. These...

This AI Paper Introduces DSPy: A Programming Model that Abstracts Language Model Pipelines as Text Transformation Graphs

AI Shorts
Language models (LMs) have given researchers the ability to create natural language processing systems with less data and at more advanced levels of understanding....

This AI Paper introduces FELM: Benchmarking Factuality Evaluation of Large Language Models

AI Shorts
Large language models (LLMs) have experienced remarkable success, ushering in a paradigm shift in generative AI through prompting. Nevertheless, a challenge associated with LLMs...

Google DeepMind Introduces Direct Reward Fine-Tuning (DRaFT): An Effective Artificial Intelligence Method for Fine-Tuning Diffusion Models to Maximize Differentiable Reward Functions

AI Shorts
Diffusion models have revolutionized generative modeling across various data types. However, in practical applications like generating aesthetically pleasing images from text descriptions, fine-tuning is...

Meet Concept2Box: Bridging the Gap Between High-Level Concepts and Fine-Grained Entities in Knowledge Graphs – A Dual Geometric Approach

AI Shorts
A lot of research has gone into finding ways to represent big sets of connected data, like knowledge graphs. These methods are called Knowledge...

This Research Paper Introduces Lavie: High-Quality Video Generation with Cascaded Latent Diffusion Models

AI Shorts
In recent years, Diffusion Models (DMs) have made significant strides in the realm of image synthesis. This has led to a heightened focus on...

This AI Paper Introduces VidChapters-7M: A Scalable Approach to Segmenting Videos into Chapters Using User-Annotated Data

AI Shorts
In the realm of video content organization, the segmentation of lengthy videos into chapters emerges as an important capability, allowing users to pinpoint their...

Unlocking Multimodal AI with Open AI: GPT-4V’s Vision Integration and Its Impact

AI Shorts
GPT-4 with vision, known as GPT-4V, empowers users to instruct the model to analyse images provided by the user. This integration of image analysis...

Meet LMSYS-Chat-1M: A Large-Scale Dataset Containing One Million Real-World Conversations with 25 State-of-the-Art LLMs

AI Shorts
Large language models (LLMs) have become integral to various AI applications, from virtual assistants to code generation. Users adapt their behavior when engaging with...

Microsoft Researchers Introduce Kosmos-2.5: A Multimodal Literate Model for Machine Reading of Text-Intensive Images

AI Shorts
In recent years, large language models (LLMs) have gained prominence in artificial intelligence, but they have mainly focused on text and struggled with understanding...

Large Language Models Surprise Meta AI Researchers at Compiler Optimization!

AI Shorts
“We thought this would be a paper about the obvious failings of LLMs that would serve as motivation for future clever ideas to overcome...
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