Research Seminar in Language Technology

20152016 / 20162017 / 20172018 / 20182019 / 20192020 / 20202021 / 20212022 / 20222023 / 2023-2024

General Information

This is the time table of the general research seminar in language technology for the spring 2024. Presentations will be given primarily by doctoral students but also other researchers in language technology including external guests We will alternate between online seminars (on zoom) and in-person seminars at the University of Helsinki. The latter may be broadcasted as well to make it possible to follow on-line. Details will be announced for each individual talk. Please, register to our mailing list below.

Place and Time:
Thursdays 14:15 – 15:45 (Metsätalo, room 26)
Live streaming: Zoom link

Registration and Announcements:
Please subscribe to our e-mail list lt-research by sending a message to majordomo@helsinki.fi with the following text in the body of your e-mail:

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Tentative Schedule – Sprint 2024

  • February 1
  • February 8: Erofili Psaltaki, University of Crete (on-site)
    • Abstract: At the beginning of this talk, I will mention the NLP projects in which I have participated. Following that, I will shift my focus to dialectology, specifically Cretan dialectology, which is my primary interest. I will present my research on Cretan interrogative elements, namely ίντα [΄i.da] and γιάντα [΄ʝa.da], examining their evolution from diachrony to synchrony.
      Notably, there is no corpus available specifically for the Cretan dialect or Greek dialects in general. Due to this limitation, I conducted my research by reading Cretan literature and folklore materials, utilizing them as my personal corpus.
      Finally, I will draw connections between this work and my master’s thesis, as it served as the inspiration for the beginning of the latter.
  • February 15: Alan Ansell, University of Cambridge (remote)
    • Title: Modular and Efficient Adaptation with Sparsity [video]
    • Abstract: Fine-tuning enables us to adapt pretrained models to specific domains and tasks. But often we are interested in combining domains and tasks, or reusing knowledge learned about one task to assist with another. Cross-lingual transfer is a typical example, where we simultaneously wish to adapt to a specific task and a specific language. In this talk, I will discuss modular and efficient fine-tuning techniques, with a focus on the sparse fine-tuning techniques I have developed during my PhD, and how they can be applied in multilingual NLP.
  • February 22: Vered Shwartz, University of British Columbia (on-site)
    • part of the mini-workshop Goodbye FoTran
    • different zoom link
    • Title: Reality Check: Natural Language Processing in the era of Large Language Models [video]
    • Abstract: Large language models (LLMs) contributed to a major breakthrough in NLP, both in terms of understanding natural language queries, commands or questions; and in generating relevant, coherent, grammatical, human-like text. LLMs like ChatGPT became a product used by many, for getting advice, writing essays, troubleshooting and writing code, creative writing, and more. This calls for a reality check: which NLP tasks did LLMs solve? What are the remaining challenges, and which new opportunities did LLMs create? In this talk, I will discuss several areas of NLP that can benefit from but are still challenging for LLMs: grounding, i.e. interpreting language based on non-linguistic context; reasoning; and real-world applications.
    • Bio: Vered Shwartz is an Assistant Professor of Computer Science at the University of British Columbia, and a CIFAR AI Chair at the Vector Institute. Her research interests include commonsense reasoning, computational semantics and pragmatics, and multiword expressions. Previously, Vered was a postdoctoral researcher at the Allen Institute for AI (AI2) and the University of Washington, and received her PhD in Computer Science from Bar-Ilan University. Vered’s work has been recognized with several awards, including The Eric and Wendy Schmidt Postdoctoral Award for Women in Mathematical and Computing Sciences, the Clore Foundation Scholarship, and an ACL 2016 outstanding paper award.
  • February 29: Dana Roemling, University of Birmingham (on-site)
    • Title: Geolinguistic Authorship Profiling in Forensic Linguistics [video]
    • Abstract: Forensic authorship profiling, i.e. the analysis of texts to infer characteristics about an author, has traditionally relied on qualitative methods and the analyst’s expertise. Consequently, this project explores how forensic authorship analyses can be advanced by employing statistical and computational methods and a large corpus of German social media posts. This project focuses on geolinguistic profiling to infer an author’s regional background by utilising regional linguistic variation 1) as a reference tool for qualitative analyses and 2) for the computational prediction of (dialect) regions. Both aim to enhance the reliability and reproducibility of forensic authorship analysis.
  • March 7 – Michal Stefanik, Masaryk University (on-site)
    • Title: Robustness of Language Models and Perspectives of Modularization[video]
    • Abstract: As the abilities of Language Models are heavily conditioned by their training data, their practical applicability shows best on data that substantially differ from their training mix. Data from other sources, often called out-of-distribution (OOD), is commonly used to evaluate models’ practical quality. In this talk, we’ll take a look at different ways to make Language Models more robust to OOD data, outlining perspective directions for low-resource scenarios. We will also discuss the blind spots of OOD evaluations that remain commonly overlooked even in very recent work. Finally, we’ll take a look at the perspective role of modularization in creating more practical and robust models, with a short survey of what the “module” can constitute, and the limitations of existing modularization techniques.
  • March 14: Tommi Buder-Gröndahl (on-site)
    • Title: Linguistic Representations in Large Language Models: Some Foundational Problems
      [video]
    • Abstract: Due to the black-box status of large language models (LLMs), increasing their explainability on a human-readable level has become as a central requirement. As part of this endeavour, numerous studies have aimed to interpret LLM-internal embeddings via familiar linguistic formalisms, such as phrase-structures or dependency graphs. The most prominent methodology here is called probing, and involves mapping embeddings (or their sequences) to pre-defined linguistic target labels. Moreover, the probing literature has regularly endorsed the idea that LLMs internally represent such linguistic structures. However, it is unclear how this claim should be interpreted in the first place: some readings of “linguistic representation” would make assigning them to LLMs trivially true, while others would make it trivially false. Finding an appropriate middle-ground is necessary for making the claim informative to begin with, but turns out to be more difficult than expected. In this presentation, I give an overview of how the problem plays out both in the standard supervised probing paradigm as well as alternative parameter-free approaches. The take-home message is that the interpretation of LLMs is likely influenced by theoretical artefacts derived from the labeling formalism, which speaks against making swift claims of linguistic representation.
  • March 21 – EACL
  • March 28 – Easter holidays
  • April 4: Wietse de Vries, Rijksuniversiteit Groningen (remote)
  • April 11: Sofoklis Kakouros (on-site)
  • April 18: Esther Ploeger, Aalborg University (on-site)
  • April 25: Jussi Karlgren, Silo.AI (on-site)
  • May 2: Janine Siewert (on-site)
  • May 9 – Ascension Day
  • May 16: John Bateman, University of Bremen (on-site)
  • May 23 – LREC/COLING
  • May 30
  • June 6: Anna Dmitrieva
  • June 13: Martijn Wieling, Rijksuniversiteit Groningen (remote)
  • June 20 – NAACL