132 citations · 163 across the 7 of their papers we have counts for
9 papers
Synthetic Data Generation and Joint Learning for Robust Code-Mixed Translation
Kartik Kartik, Sanjana Soni, Anoop Kunchukuttan +2
The widespread online communication in a modern multilingual world has provided opportunities to blend more than one language (aka code-mixed language) in a single utterance. This…
Decoding a Neural Retriever's Latent Space for Query Suggestion
Leonard Adolphs, Michelle Chen Huebscher, Christian Buck +4
Neural retrieval models have superseded classic bag-of-words methods such as BM25 as the retrieval framework of choice. However, neural systems lack the interpretability of bag-of-…
Zero-Shot Retrieval with Search Agents and Hybrid Environments
Michelle Chen Huebscher, Christian Buck, Massimiliano Ciaramita +1
Learning to search is the task of building artificial agents that learn to autonomously use a search box to find information. So far, it has been shown that current language models…
Tomayto, Tomahto. Beyond Token-level Answer Equivalence for Question Answering Evaluation
Jannis Bulian, Christian Buck, Wojciech Gajewski +2
The predictions of question answering (QA)systems are typically evaluated against manually annotated finite sets of one or more answers. This leads to a coverage limitation that re…
Boosting Search Engines with Interactive Agents
Leonard Adolphs, Benjamin Boerschinger, Christian Buck +8
This paper presents first successful steps in designing search agents that learn meta-strategies for iterative query refinement in information-seeking tasks. Our approach uses mach…
Meta Answering for Machine Reading
Benjamin Borschinger, Jordan Boyd-Graber, Christian Buck +7
We investigate a framework for machine reading, inspired by real world information-seeking problems, where a meta question answering system interacts with a black box environment.…