Dear Michael
Since I have been kind of "at it" on NLP, I thought to be fair to not miss
out on this call, I hope similar calls could find these remarks useful:
i. NLP as CHI (Computer-Human Interaction) is fine;
ii. some information can be extracted based on text, not all; (there might
also be a "culture/disciplinary/technical gap" on the term "meaning";)
iii. some or a few text-based phenomena can be captured in
statistical/machine learning (if one knows what and how --- without
tokenization and with full data (i.e. without discarding any data) --- this
can be considered advanced research or the next goalpost compared to what
has been customarily done in "NLP"). Most text-based phenomena, claimed in
"NLP" thus far, may not really need ML or be compatible with ML, esp. if
there are no statistical correlates.
I suppose NLP is still an explicit re-evaluation phase. There is much to
clean up. It is important to examine more carefully the interaction between
statistical/numerical and textual values.
Thanks for bearing with me and my remarks here.
Best
Ada
On Mon, Aug 28, 2023 at 11:08 AM Michael Roth (Saarland University) via
Corpora <corpora@list.elra.info> wrote:
> The independent research group on
>
> "Computational Models of Misunderstanding for Complex Instructional Text"
>
> invites applications for one research associate. The position is funded
> through a grant in the Emmy Noether Programme of the German Research
> Foundation (DFG---Deutsche Forschungsgemeinschaft), which funds projects
> similar to an ERC Starting Grant or NSF CAREER Award. The group is headed
> by Dr. Michael Roth and currently hosted by the Institute for Natural
> Language Processing ("IMS") at the University of Stuttgart, Germany [1
> <https://www.ims.uni-stuttgart.de/en/institute/researchgroups/mist/>].
>
> The project is concerned with the systematic analysis and computational
> modelling of text passages that can lead to misunderstandings. A
> substantial amount of previous work has studied misunderstandings in
> dialogue, but suitable resources for written language are scarce because
> misunderstandings cannot be observed directly from a text. Since readers
> and writers typically do not interact, it is important for authors to
> ensure that texts leave no room for misinterpretation. Otherwise, for
> example, medical instructions may be followed incorrectly, and route
> directions may not guide navigators to their desired destination.
>
> The announced position plays a key role in the project's final phase,
> leveraging previously created resources (e.g. [2
> <https://aclanthology.org/2022.lrec-1.354/>,3
> <https://aclanthology.org/2020.lrec-1.702/>]) and connecting to the
> group's award-winning earlier work (e.g. [4
> <https://aclanthology.org/2021.eacl-srw.5/>,5
> <https://aclanthology.org/2022.semeval-1.146/>]). Potential areas of
> focus for the successful candidate include delving deeper into specific
> linguistic factors that may lead to misunderstandings (such as elements of
> implicit or underspecified language), enhancing classification models by
> incorporating additional information (such as commonsense knowledge or
> multi-modal context), and/or testing these models in practical applications
> (such as question answering or machine translation). The position is
> initially available until February 2025, with a start date as soon as
> possible (e.g. December 2023) and the possibility of extension (for a total
> of at least 2 years). Compensation will be in accordance with the German
> TV-L E13 salary scale at 100% (approx. 4,000 EUR *gross* per month).
>
> Successful applicants will have obtained a Ph.D. (or are close to
> completing their thesis) in computational linguistics, machine learning, or
> a closely related field, with a particular interest in semantics and
> pragmatics or downstream applications. Programming skills and the ability
> to work in a team are taken for granted. The candidate should be able to
> work and communicate in English (no proficiency of German is required).
> Applications should include a motivation letter including research
> interests, a CV, a list of publications and contact information of up to
> three references. Applications should be sent *as a single PDF file* to
> Michael Roth by email. Applications received by 23 September 2023 will
> receive full consideration, but the position will remain open until filled.
>
> Candidates who identify as female, LGBTQ+ and/or as members of any
> underrepresented group are particularly encouraged to apply. Feel free to
> contact Michael Roth (head of group) or Nicola Fanton (PhD student) for any
> question regarding the group or position.
>
> [1] https://www.ims.uni-stuttgart.de/en/institute/researchgroups/mist/
> [2] https://aclanthology.org/2022.lrec-1.354/
> [3] https://aclanthology.org/2020.lrec-1.702/
> [4] https://aclanthology.org/2021.eacl-srw.5/ (best student paper)
> [5] https://aclanthology.org/2022.semeval-1.146/ (best task description
> paper)
>
>
> --
> Dr. Michael Roth
> Emmy Noether Group Leader
> Institute for Natural Language Processing
> University of Stuttgart
>
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