ZurichCV Meetup #3
2024-06-13 18:00 - 20:00 (Europe/Paris) | OAT ETH Zürich (14th Floor), Andreasstrasse 5 (14th floor), Zurich, 8050
ZurichCV #3 on June 13th at 18:00 will feature two talks:

Julian Schilliger from ETH Zurich on deciphering ancient papyrus for the Scroll Prize (Vesuvius Challenge):
“On how to unroll and read a 2000 year old papyrus scroll that was buried by the Vesuvius eruption with computer vision, from ancient Rome to a modern particle accelerator and into an high resolution and large CT scan of the scroll.”
Nicolas Muntwyler from nunu.ai on building visual agents to playtest video games

RSVP soon. See you there!

ZurichNLP Meetup #10
2024-05-28 18:00 - 20:00 (Europe/Paris) | OAT ETH Zürich (14th Floor), Andreasstrasse 5 (14th floor), Zurich, 8050
We’re happy to announce ZurichNLP #10 on May 28th with the following speakers:

Kacper Lukawski (Senior Developer Advocate @ Qdrant) on optimizing RAG applications:
“LLM outputs in the Retrieval Augmented Generation pipelines are only as good as the documents we provide for answer generation. We will review the strategies of semantic search optimization depending on your speed, memory, and quality requirements”
Tannon Kew (PhD student @ University of Zurich) on tuning English-centric LLMs into polyglots

RSVP soon as spots are limited.

ZurichNLP Meetup #9
2024-04-25 18:00 - 20:00 (Europe/Paris) | OAT ETH Zürich (14th Floor), Andreasstrasse 5 (14th floor), Zurich, 8050
We’re happy to announce ZurichNLP #9 on April 25th with the following speakers:

Lewis Tunstall (MLE @ HuggingFace) on How to Align Your LLM
Vilém Zouhar (PhD @ ETH Zurich) on Pride and BPE: How We Solved Tokenization but Got It Wrong
“Tokenization is present in almost all NLP pipelines, but rarely examined mathematically. We formalize and show boundaries to the most popular tokenization algorithm, Byte-Pair Encoding. Then, with information theory, we show what makes some tokenization better than others and how to use this as a metric before training your expensive models. Lastly, we admit how we got this hypothesis wrong.”

Slides from Lewis’s presentation can be found here!
RSVP soon as spots are limited.

ZurichCV Meetup #2
2024-04-16 17:00 - 20:00 (Europe/Paris) | OAT ETH Zürich (14th Floor), Andreasstrasse 5 (14th floor), Zurich, 8050
Our computer vision series is continuing strong: ZurichCV #2 on April 16th at 17:00 will feature an in depth talk by Lucas Beyer from Google Brain/DeepMind about structured computer vision in the age of LLMs, specifically:
“Structured output tasks in computer vision are tasks which require more “complicated” output than just a probability, and need to be “globally consistent”. Examples are detection, (panoptic) segmentation, colorization, tracking, and many more. Classically, communities have formed around each such task, with their very specialized approaches. We take a step back, understand why, and devise a general solution, that is surprisingly similar to LLMs, hence bringing the communities closer together. Papers covered: https://arxiv.org/abs/2205.10337 and https://arxiv.org/abs/2302.08242.”
RSVP soon. See you there!

ZurichCV Meetup #1
2024-03-14 18:00 - 20:00 (Europe/Paris) | OAT ETH Zürich (14th Floor), Andreasstrasse 5 (14th floor), Zurich, 8050
With all of the success with ZurichNLP we are now kicking off our first ZurichCV meetup this upcoming March 14th (Pi day)! Our first meetup will feature the following speakers:

Felix Bauer, Senior R&D Engineer at SynSense
Songyou Peng, Senior Researcher/Postdoc at ETH Zurich

Please RSVP as soon as possible because spots fill up quick, hope to see you there!

ZurichNLP Meetup #8
2024-02-27 18:00 - 20:00 (Europe/Paris) | OAT ETH Zürich (14th Floor), Andreasstrasse 5 (14th floor), Zurich, 8050
We are continuing strong in 2024 with Meetup #8 on February 27th! We’re happy to announce the following speakers:

Brian DuSell, Postdoc @ ETH Zurich
Leandro von Werra, Chief Loss Officer @ Hugging Face

RSVP soon as spots are limited, the last few times we maxed out capacity. Talk details:
Speaker #1: Brian DuSell
Title: Stack Attention: Improving the Ability of Transformers to Model Hierarchical Patterns
Summary: Language contains hierarchical syntactic patterns, but transformers do not have a mechanism for dealing with hierarchies of arbitrary depth. In this talk I will present my work on Stack Attention, a kind of self-attention with a latent model of syntax that addresses this limitation and allows transformers to model any context-free language.
Speaker #2: Leandro von Werra
Title: BigCode: Building LLM’s for Code in an Open and Responsible Way
Hope to see you there!

ZurichNLP Meetup #7
2024-01-16 18:00 - 20:00 (Europe/Paris) | OAT ETH Zürich (14th Floor), Andreasstrasse 5 (14th floor), Zurich, 8050
Happy new year! We are kicking off 2024 with Meetup #7 on January 16th! It’s our pleasure to announce the following speakers:

Martina Forster and Luca Campanella from Typewise
Tiago Pimentel from ETH Zurich

RSVP soon as spots are limited, the last few times we maxed out capacity. Talk details:
Speaker #1: Martina Forster and Luca Campanella
Title: Life in an NLP Startup: A Glimpse into Typewise’s Journey in Revolutionizing Customer Service
Abstract: Ever wondered what it’s like to work in an NLP startup in Switzerland? Join us as we share our experiences at Typewise, a Zurich-based startup that’s transforming customer service with AI. We’ll give you a taste of our day-to-day, the challenges we face, and the excitement of working in the rapidly evolving field of NLP. You’ll also get a sneak peek of our text prediction technology and how it’s making customer service communication more efficient. Plus, we’ll dive into one of the NLP tasks we work on – Grammatical Error Correction. If you’re curious about the practical applications of AI and the realities of working in an NLP startup, this talk is for you.
Speaker #2: Tiago Pimentel
Title: Revisiting the Optimality of Word Lengths
Zipf posited that wordforms are optimized to minimize utterances’ communicative costs. He supported this claim by showing that words’ lengths are inversely correlated with their frequencies. This correlation, however, is only expected if one assumes that a words’ communicative cost is given by its length. We explore this assumption, comparing the predictive power over word lengths we get when assuming different operationalisations of communicative cost.
Hope to see you there!

ZurichNLP Meetup #6
2023-12-07 17:00 - 19:00 (Europe/Paris) | OAT ETH Zürich (14th Floor), Andreasstrasse 5 (14th floor), Zurich, 8050
Meetup #6 is coming soon and will be our best one yet! It’s our pleasure to announce the following speakers:

Lucas Beyer (Google DeepMind/Brain)
Ana Kotarcic (University of Zurich)

RSVP soon as spots are limited, the last few times we maxed out capacity. Hope to see you there!

ZurichNLP Meetup #5
2023-10-19 18:00 - 20:00 (Europe/Paris) | OAT ETH Zürich, Andreasstrasse 5 (19th floor), Zurich, 8050
Meetup #5 is fast approaching and will be our best one yet! It’s our pleasure to announce the following speakers:

Jonas Pfeiffer, Research Scientist at Deepmind presenting “Modular Deep Learning“
Eiso Kant, CTO and Co-founder of Poolside presenting “Roadmap for AI progress by learning from code”

RSVP soon as spots are limited, last time we maxed capacity. Hope to see you there!

How Does the Brain Create Language?
2023-10-02 16:15 - 17:15 (Europe/Paris) | ETH Zurich CAB, Universitätstrasse 6 (CAB G.61), Zürich, 8006, Switzerland
ETH Zurich Distinguished Computer Science Colloquium
Christos Papadimitriou, Columbia University
Host: Emo Welzl
ABSTRACT:
There is little doubt that cognitive phenomena are the result of neural activity, and yet there has been slow progress toward articulating a computational theory of how exactly this happens. I will discuss a simplified mathematical model of the brain, which we call NEMO, involving brain areas, spiking neurons, random synapses, local inhibition, Hebbian plasticity, and long-range interneurons – crucially, there is no backpropagation in NEMO. Emergent behaviors of the resulting dynamical system – established both analytically and through simulations – include assemblies of neurons, sequence memorization, one-shot learning, and universal computation. NEMO is also a software-based neuromorphic system that can be simulated efficiently at the scale of tens of millions of neurons, emulating certain high-level cognitive phenomena such as planning and parsing of natural language. I will describe current work aiming at creating through NEMO a neuromorphic language organ: a neural tabula rasa which, on input consisting of a modest amount of grounded language, is capable of language acquisition: learning lexicon, syntax, semantics, comprehension, and generation. Finally, and on the plane of scientific methodology, I will argue that experimenting with such brain-like devices, devoid of backpropagation, can reveal novel avenues to learning, and may end up advancing AI.
BIOGRAPHY:
Christos Harilaos Papadimitriou is the Donovan Family Professor of Computer Science at Columbia University. Before joining Columbia in 2017, he was a professor at UC Berkeley for the previous 22 years, and before that he taught at Harvard, MIT, NTU Athens, Stanford, and UCSD. He has written five textbooks and many articles on algorithms and complexity, and their applications to optimization, databases, control, AI, robotics, economics and game theory, the Internet, evolution, and the brain. He holds a PhD from Princeton (1976), and nine honorary doctorates, including from ETH, University of Athens, EPFL, and Univ. de Paris Dauphine. He is a member of the National Academy of Sciences of the US, the American Academy of Arts and Sciences, and the National Academy of Engineering, and he has received the Knuth prize, the Gödel prize, the Babbage award, the von Neumann medal, the IEEE women of the Edvac Computer Pioneer Award, as well as the 2018 Harvey Prize by Technion. In 2015 the president of the Hellenic Republic named him commander of the order of the Phoenix. He has also written three novels: “Turing,” “Logicomix” and his latest “Independence.”

ZurichNLP Meetup #4
2023-09-26 18:00 - 20:00 (Europe/Paris) | OAT ETH Zürich, Andreasstrasse 5 (19th floor), Zurich, 8050
We’re back with an exciting fourth meetup! We are thrilled to be hosting two talks:

“Reinforced Active Learning for Text classification” by Katya Mirylenka from IBM Research.
“AI Summarizers for Lawyers and the People” by Prof. Dr. Elliott Ash from ETH Zurich

RSVP soon as spots are limited, we hope to see you there!

ZurichNLP Meetup #3
2023-06-27 18:00 - 20:00 (Europe/Paris) | OAT ETH Zürich, Andreasstrasse 5 (19th floor), Zurich, 8050
Join us for our third meetup this time with an exciting fireside chat between Tim Scarfe and Zeerak Talat on democratization of AI, policy and ethics. The panel is being rescheduled to sometime this fall.
Please RSVP, spots are limited!

ZürichNLP Visitors: Niket Tandon
2023-06-05 18:00 - 19:00 (Europe/Paris) | OAT ETH Zürich, Andreasstrasse 5 (19th floor), Zurich, 8050
Niket Tandon from AI2 will be visiting Zurich in June and will be giving a talk titled Commonsense injection in large language models. Please RSVP below!
Abstract: Large LMs, while powerful, are not immune to mistakes which are obvious to humans, but they can be prohibitively costly to retrain. Our goal is to effectively correct language model mistakes by injecting knowledge via user interactions with the system but without retraining. Our approach is a memory-augmented architecture, where user feedback is used to make the model generate a better answer or to post hoc correct the errors such that the model does not repeat similar mistakes. We will discuss efficient solutions to designing this memory of knowledge, and leveraging it in the model. This is a step in the direction of never ending learning, and we will present a future roadmap to what open research problems need to be addressed to get to never ending learning language models.
Bio: Niket Tandon is a Senior Research Scientist at the Allen Institute for AI in Seattle. His research interests are in commonsense reasoning and natural language guided reasoning. He works at the Aristo team responsible for creating AI which aced science exams. He obtained his Ph.D. from the Max Planck Institute for Informatics in Germany in 2016, where he was supervised by Professor Gerhard Weikum, resulting in the largest automatically extracted commonsense knowledge base at the time, called WebChild. He is also the founder of PQRS research, an organization providing research opportunities to undergraduate students from underrepresented institutes.
Homepage: https://niket.tandon.info/

ZurichNLP Meetup #2
2023-05-10 18:00 - 20:00 (Europe/Helsinki) | OAT ETH Zürich, Andreasstrasse 5 (19th floor), Zurich, 8050
Coming off the success of our first meetup, we welcome all NLP researchers, engineers and enthusiasts to our second event. We have two really exciting guests presenting: Julian Eisenschlos from Google and Alex Warstadt from ETH Zurich.
Please RSVP, spots are limited!
Follow us on Twitter for updates.

Modular and Parameter-Efficient Fine-Tuning for NLP Models
2023-04-26 16:45 (Europe/Paris) | University of Zurich AND (Room 2-02), Andreasstrasse 15, Zurich, 8050, Switzerland
Summary: State-of-the-art language models in NLP perform best when fine-tuned even on small datasets, but due to their increasing size, fine-tuning and downstream usage have become extremely compute-intensive. Being able to efficiently and effectively fine-tune the largest pre-trained models is thus key in order to reap the benefits of the latest advances in NLP. In this tutorial, we provide a comprehensive overview of parameter-efficient fine-tuning methods. We highlight their similarities and differences by presenting them in a unified view. We explore the benefits and usage scenarios of a neglected property of such parameter-efficient models—modularity—such as composition of modules to deal with previously unseen data conditions. We finally highlight how both properties——parameter efficiency and modularity——can be useful in the real-world setting of adapting pre-trained models to under-represented languages and domains with scarce annotated data for several downstream applications.
Speaker: Jonas Pfeiffer is a Research Scientist at Google Research. He is interested in modular representation learning in multi-task, multilingual, and multi-modal contexts, and in low-resource scenarios. He worked on his PhD at the Technical University of Darmstadt, was a visiting researcher at the New York University and a Research Scientist Intern at Meta Research. Jonas has received the IBM PhD Research Fellowship award for 2021/2022. He has given numerous invited talks at academia, industry and ML summer schools, and has co-organized multiple workshops on multilinguality and multimodality.
Also available online: https://uzh.zoom.us/j/62400025916?pwd=[REDACTED]
Additional Information: Guest lecture for the seminar course “Multimodal Multilingual Natural Language Processing”. We will have a small Apero after the talk in the CL coffee lounge. There will be drinks and some snacks.

ZurichNLP Meetup #1
2023-03-21 18:00 - 20:00 (Europe/Paris) | ETH Zurich, Binzmühlestrasse 13, Zurich, 8050, Switzerland
We are doing our first kick-off event on March 21st from 6:00 – 8:00 PM at Binzmühlestrasse 13, 4th Floor, 8050 Zürich
We are very excited to be hosting two speakers, Luca Beurer-Kellner from the SRI lab at ETH Zurich and Basil Mustafa from Google Brain Zurich Looking forward to seeing you there!
