4 citations · 8 across the 12 of their papers we have counts for
12 papers
A Continuous-Time Markov Chain Framework for Insertion Language Models
Dhruvesh Patel, Benjamin Rozonoyer, Soumitra Das +3
Insertion Language Models (ILMs) offer several advantages over left-to-right generation and mask-based generation. However, existing formulations of insertion-based generation have…
Learned Relay Representations for Forward-Thinking Discrete Diffusion Models
Benjamin Rozonoyer, Jacopo Minniti, Dhruvesh Patel +4
When Masked Diffusion Models (MDMs) generate sequences through iterative refinement, the rich internal computation over masked positions is discarded, forcing every subsequent refi…
Insertion Based Sequence Generation with Learnable Order Dynamics
Dhruvesh Patel, Benjamin Rozonoyer, Gaurav Pandey +3
Existing insertion-based masked diffusion models that generate sequences by interleaving token insertion with unmasking use fixed schedules that are not dependent on the data. For…
XLM: A Python package for non-autoregressive language models
Dhruvesh Patel, Durga Prasad Maram, Sai Sreenivas Chintha +2
In recent years, there has been a resurgence of interest in non-autoregressive text generation in the context of general language modeling. Unlike the well-established autoregressi…
Insertion Language Models: Sequence Generation with Arbitrary-Position Insertions
Dhruvesh Patel, Aishwarya Sahoo, Avinash Amballa +3
Autoregressive models (ARMs), which predict subsequent tokens one-by-one ``from left to right,'' have achieved significant success across a wide range of sequence generation tasks.…
Language Guided Exploration for RL Agents in Text Environments
Hitesh Golchha, Sahil Yerawar, Dhruvesh Patel +2
Real-world sequential decision making is characterized by sparse rewards and large decision spaces, posing significant difficulty for experiential learning systems like $\textit{ta…
Pretrained Language Models as Visual Planners for Human Assistance
Dhruvesh Patel, Hamid Eghbalzadeh, Nitin Kamra +3
In our pursuit of advancing multi-modal AI assistants capable of guiding users to achieve complex multi-step goals, we propose the task of "Visual Planning for Assistance (VPA)". G…
Box Embeddings: An open-source library for representation learning using geometric structures
Tejas Chheda, Purujit Goyal, Trang Tran +4
A major factor contributing to the success of modern representation learning is the ease of performing various vector operations. Recently, objects with geometric structures (eg. d…
Word2Box: Capturing Set-Theoretic Semantics of Words using Box Embeddings
Shib Sankar Dasgupta, Michael Boratko, Siddhartha Mishra +4
Learning representations of words in a continuous space is perhaps the most fundamental task in NLP, however words interact in ways much richer than vector dot product similarity c…
Weakly Supervised Medication Regimen Extraction from Medical Conversations
Dhruvesh Patel, Sandeep Konam, Sai P. Selvaraj
Automated Medication Regimen (MR) extraction from medical conversations can not only improve recall and help patients follow through with their care plan, but also reduce the docum…
Reading Comprehension as Natural Language Inference: A Semantic Analysis
Anshuman Mishra, Dhruvesh Patel, Aparna Vijayakumar +3
In the recent past, Natural language Inference (NLI) has gained significant attention, particularly given its promise for downstream NLP tasks. However, its true impact is limited…
Looking Beyond Sentence-Level Natural Language Inference for Downstream Tasks
Anshuman Mishra, Dhruvesh Patel, Aparna Vijayakumar +3
In recent years, the Natural Language Inference (NLI) task has garnered significant attention, with new datasets and models achieving near human-level performance on it. However, t…