--- title: "Arun Raja — author profile and papers" description: "Arun Raja, Institute for Infocomm Research: 2 papers on Elamur Research (2021), h-index 2 — affiliations, topics, co-authors and who cites them in our…" canonical: "https://research.elamur.ai/free/en/authors/arun-raja/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/arun-raja/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Arun Raja # Arun Raja Arun Raja works in natural language processing, and their papers here centre on large language models. One question is how such models can cope with tasks they were never directly trained on. The other is which units of text a model should read and produce in the first place. The methods range from assembling large collections of prompted training data to surveying long lines of research on [tokenization and segmentation](https://md.research.elamur.ai/free/en/topics/tokenization/). The most cited of these works is [Multitask Prompted Training Enables Zero-Shot Task Generalization](https://md.research.elamur.ai/free/en/papers/sanh-2021-multitask-prompted-training-enables-zero/). It asks whether the zero-shot abilities seen in very large models can be produced on purpose by explicitly training on many tasks at once, rather than left to whatever task-like text a pretraining corpus happens to contain. To do this, the authors created PromptSource, which combines a templating language with an openly available crowdsourcing tool. They used it to recast many English datasets as natural-language inputs paired with targets, each dataset receiving several prompts phrased in different ways. The datasets were then sorted by their format into task families, so that entire families could be kept aside for evaluation. The second work, [Between words and characters](https://md.research.elamur.ai/free/en/papers/mielke-2021-between-words-characters-brief-history/), is a survey written by the tokenization working group of the BigScience Workshop. It draws pre-neural and neural research into one account. It untangles related notions such as typographic tokens, word forms and subwords, and covers hybrid word–character models, subword methods like BPE, WordPiece and Unigram LM, and approaches built on characters, bytes or even pixels. Both papers here date from 2021, so they mark a single moment in the work. That moment joins large-scale prompted training with a close look at how text is divided into units. Raja is affiliated with the [Institute for Infocomm Research](https://md.research.elamur.ai/free/en/labs/institute-for-infocomm-research/) in Singapore. Frequent co-authors include [Colin Raffel](https://md.research.elamur.ai/free/en/authors/colin-raffel/), [Manan Dey](https://md.research.elamur.ai/free/en/authors/manan-dey/) and [Zaid Alyafeai](https://md.research.elamur.ai/free/en/authors/zaid-alyafeai/). Other collaborators on these papers include [Sabrina J. Mielke](https://md.research.elamur.ai/free/en/authors/sabrina-j-mielke/) and [Benoît Sagot](https://md.research.elamur.ai/free/en/authors/benoit-sagot/). Arun Raja has 2 papers in our library, in 2021, most of them on [Tokenization & segmentation](https://md.research.elamur.ai/free/en/topics/tokenization/); often with [Colin Raffel](https://md.research.elamur.ai/free/en/authors/colin-raffel/), [Manan Dey](https://md.research.elamur.ai/free/en/authors/manan-dey/), [Zaid Alyafeai](https://md.research.elamur.ai/free/en/authors/zaid-alyafeai/). 2 papers in our library · 2021 [OpenAlex](https://openalex.org/A5073058818) · [**h-index 2**](https://openalex.org/authors/A5073058818) · [2 works](https://openalex.org/works?filter=author.id:A5073058818) · [551 citations](https://openalex.org/works?filter=author.id:A5073058818&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/arun-raja/#papers) · [🔗 1,117 citations in our library](https://md.research.elamur.ai/free/en/authors/arun-raja/cited-by/) · [⭐ Paper Star rank #1381](https://md.research.elamur.ai/free/en/paper-stars/page/14/#star-1381) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Arun+Raja) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Arun+Raja) · [dblp](https://dblp.org/search?q=Arun+Raja) · [ACL Anthology](https://aclanthology.org/search/?q=Arun+Raja) ## Affiliations [🔬**Institute for Infocomm Research** Singapore · Singapore 2021 · 1 paper*current*](https://md.research.elamur.ai/free/en/labs/institute-for-infocomm-research/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. ## Concepts, shelves and topics Of its works in our library: the number of works on each and its rating among them. 💡 Concepts 1[Subword tokenization · 1 work](https://md.research.elamur.ai/free/en/concepts/subword-tokenization/) 📚 Shelves 2[Other · 1 work](https://md.research.elamur.ai/free/en/shelves/other/) · [AI & machine learning · 1 work](https://md.research.elamur.ai/free/en/shelves/ai/) 🧭 Topics 1[Tokenization & segmentation · 1 work](https://md.research.elamur.ai/free/en/topics/tokenization/) ## Works by year ### 2020s [**2021** 2 papers](https://md.research.elamur.ai/free/en/authors/arun-raja/year/2021/) ## Papers The most cited first (OpenAlex and our library). 1. **[Multitask Prompted Training Enables Zero-Shot Task Generalization](https://md.research.elamur.ai/free/en/papers/sanh-2021-multitask-prompted-training-enables-zero/)** *(2021 · 1,577 citations)* Large language models such as GPT-3 can handle unseen tasks zero-shot. However, this ability shows up only at large scale and depends heavily on how a prompt is phrased. The authors ask whether such generalization can be produced deliberately through explicit supervised multitask training, rather than relying on… 2. **[Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLP](https://md.research.elamur.ai/free/en/papers/mielke-2021-between-words-characters-brief-history/)** *(2021 · 89 citations)* This is a survey paper by the BigScience Workshop tokenization working group. The authors examine which units of text NLP models should operate on: words, subwords, characters, bytes, or even pixels. The paper offers no new data and no method of its own. Instead, it connects research from the pre-neural and neural… ## Co-authors here 12 of 15 co-authors with a page, the most papers together first. - [Colin Raffel](https://md.research.elamur.ai/free/en/authors/colin-raffel/) ×2 - [Manan Dey](https://md.research.elamur.ai/free/en/authors/manan-dey/) ×2 - [Zaid Alyafeai](https://md.research.elamur.ai/free/en/authors/zaid-alyafeai/) ×2 - [Albert Webson](https://md.research.elamur.ai/free/en/authors/albert-webson/) - [Antoine Chaffin](https://md.research.elamur.ai/free/en/authors/antoine-chaffin/) - [Benoît Sagot](https://md.research.elamur.ai/free/en/authors/benoit-sagot/) - [Chenglei Si](https://md.research.elamur.ai/free/en/authors/chenglei-si/) - [Elizabeth Salesky](https://md.research.elamur.ai/free/en/authors/elizabeth-salesky/) - [Lintang Sutawika](https://md.research.elamur.ai/free/en/authors/lintang-sutawika/) - [M Saiful Bari](https://md.research.elamur.ai/free/en/authors/m-saiful-bari/) - [Sabrina J. Mielke](https://md.research.elamur.ai/free/en/authors/sabrina-j-mielke/) - [Samson Tan](https://md.research.elamur.ai/free/en/authors/samson-tan/) ## Cited by Papers of our library cite their works 1,117 times (of the 140,884 papers whose bibliographies we read); [143 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/arun-raja/cited-by/). Updated 23 October 2026