Tootfinder

The Surprising Effectiveness of Rankers Trained on Expanded Queries
Abhijit Anand, Venktesh V, Vinay Setty, Avishek Anand
https://arxiv.org/abs/2404.02587 …

The Surprising Effectiveness of Rankers Trained on Expanded Queries
An important problem in text-ranking systems is handling the hard queries that form the tail end of the query distribution. The difficulty may arise due to the presence of uncommon, underspecified, or incomplete queries. In this work, we improve the ranking performance of hard or difficult queries without compromising the performance of other queries. Firstly, we do LLM based query enrichment for training queries using relevant documents. Next, a specialized ranker is fine-tuned only on the enr…

Convolutional Prompting meets Language Models for Continual Learning
Anurag Roy, Riddhiman Moulick, Vinay K. Verma, Saptarshi Ghosh, Abir Das
https://arxiv.org/abs/2403.20317

Convolutional Prompting meets Language Models for Continual Learning
Continual Learning (CL) enables machine learning models to learn from continuously shifting new training data in absence of data from old tasks. Recently, pretrained vision transformers combined with prompt tuning have shown promise for overcoming catastrophic forgetting in CL. These approaches rely on a pool of learnable prompts which can be inefficient in sharing knowledge across tasks leading to inferior performance. In addition, the lack of fine-grained layer specific prompts does not allow…

FactCheck Editor: Multilingual Text Editor with End-to-End fact-checking
Vinay Setty
https://arxiv.org/abs/2404.19482 https://arxiv.org/pdf/2404.19482
arXiv:2404.19482v1 Announce Type: new
Abstract: We introduce 'FactCheck Editor', an advanced text editor designed to automate fact-checking and correct factual inaccuracies. Given the widespread issue of misinformation, often a result of unintentional mistakes by content creators, our tool aims to address this challenge. It supports over 90 languages and utilizes transformer models to assist humans in the labor-intensive process of fact verification. This demonstration showcases a complete workflow that detects text claims in need of verification, generates relevant search engine queries, and retrieves appropriate documents from the web. It employs Natural Language Inference (NLI) to predict the veracity of claims and uses LLMs to summarize the evidence and suggest textual revisions to correct any errors in the text. Additionally, the effectiveness of models used in claim detection and veracity assessment is evaluated across multiple languages.

Krylov Complexity in $2d$ CFTs with SL$(2,\mathbb{R})$ deformed Hamiltonians
Vinay Malvimat, Somnath Porey, Baishali Roy
https://arxiv.org/abs/2402.15835 h…

Krylov Complexity in $2d$ CFTs with SL$(2,\mathbb{R})$ deformed Hamiltonians
In this study, we analyze Krylov Complexity in two-dimensional conformal field theories subjected to deformed SL$(2,\mathbb{R})$ Hamiltonians. In the vacuum state, we find that the K-complexity exhibits a universal phase structure. The phase structure involves the K-complexity exhibiting an oscillatory behaviour in the non-heating phase, which contrasts with the exponential growth observed in the heating phase, while it displays polynomial growth at the phase boundary. Furthermore, we extend ou…

Krylov Complexity in $2d$ CFTs with SL$(2,\mathbb{R})$ deformed Hamiltonians
Vinay Malvimat, Somnath Porey, Baishali Roy
https://arxiv.org/abs/2402.15835 h…

Krylov Complexity in $2d$ CFTs with SL$(2,\mathbb{R})$ deformed Hamiltonians
In this study, we analyze Krylov Complexity in two-dimensional conformal field theories subjected to deformed SL$(2,\mathbb{R})$ Hamiltonians. In the vacuum state, we find that the K-complexity exhibits a universal phase structure. The phase structure involves the K-complexity exhibiting an oscillatory behaviour in the non-heating phase, which contrasts with the exponential growth observed in the heating phase, while it displays polynomial growth at the phase boundary. Furthermore, we extend ou…

Towards Joint Optimization for DNN Architecture and Configuration for Compute-In-Memory Hardware
Souvik Kundu, Anthony Sarah, Vinay Joshi, Om J Omer, Sreenivas Subramoney
https://arxiv.org/abs/2402.11780

Towards Joint Optimization for DNN Architecture and Configuration for Compute-In-Memory Hardware
With the recent growth in demand for large-scale deep neural networks, compute in-memory (CiM) has come up as a prominent solution to alleviate bandwidth and on-chip interconnect bottlenecks that constrain Von-Neuman architectures. However, the construction of CiM hardware poses a challenge as any specific memory hierarchy in terms of cache sizes and memory bandwidth at different interfaces may not be ideally matched to any neural network's attributes such as tensor dimension and arithmetic int…

Effect of Systematic Uncertainties on Density and Temperature Estimates in Coronae of Capella
Xixi Yu, Vinay L. Kashyap, Giulio Del Zanna, David A. van Dyk, David C. Stenning, Connor P. Ballance, Harry P. Warren
https://arxiv.org/abs/2404.10427

Effect of Systematic Uncertainties on Density and Temperature Estimates in Coronae of Capella
We estimate the coronal density of Capella using the O VII and Fe XVII line systems in the soft X-ray regime that have been observed over the course of the Chandra mission. Our analysis combines measures of error due to uncertainty in the underlying atomic data with statistical errors in the Chandra data to derive meaningful overall uncertainties on the plasma density of the coronae of Capella. We consider two Bayesian frameworks. First, the so-called pragmatic-Bayesian approach considers the a…

Joint Deconvolution of Astronomical Images in the Presence of Poisson Noise
Axel Donath, Aneta Siemiginowska, Vinay L. Kashyap, David A. van Dyk, Douglas Burke
https://arxiv.org/abs/2403.13933

Joint Deconvolution of Astronomical Images in the Presence of Poisson Noise
We present a new method for joint likelihood deconvolution (Jolideco) of a set of astronomical observations of the same sky region in the presence of Poisson noise. The observations may be obtained from different instruments with different resolution, and different point spread functions. Jolideco reconstructs a single flux image by optimizing the posterior distribution based on the joint Poisson likelihood of all observations under a patch-based image prior. The patch prior is parameterised vi…

PKG API: A Tool for Personal Knowledge Graph Management
Nolwenn Bernard, Ivica Kostric, Weronika {\L}ajewska, Krisztian Balog, Petra Galu\v{s}\v{c}\'akov\'a, Vinay Setty, Martin G. Skj{\ae}veland
https://arxiv.org/abs/2402.07540

PKG API: A Tool for Personal Knowledge Graph Management
Personal knowledge graphs (PKGs) offer individuals a way to store and consolidate their fragmented personal data in a central place, improving service personalization while maintaining full user control. Despite their potential, practical PKG implementations with user-friendly interfaces remain scarce. This work addresses this gap by proposing a complete solution to represent, manage, and interface with PKGs. Our approach includes (1) a user-facing PKG Client, enabling end-users to administer t…

Accessibility in Information Retrieval
Leif Azzopardi, Vishwa Vinay
https://arxiv.org/abs/2404.08628 https://arxiv.org/pdf/2404.08628…

Accessibility in Information Retrieval
This paper introduces the concept of accessibility from the field of transportation planning and adopts it within the context of Information Retrieval (IR). An analogy is drawn between the fields, which motivates the development of document accessibility measures for IR systems. Considering the accessibility of documents within a collection given an IR System provides a different perspective on the analysis and evaluation of such systems which could be used to inform the design, tuning and mana…