diff --git a/README.md b/README.md
index 7026e38..3326e0d 100644
--- a/README.md
+++ b/README.md
@@ -44,6 +44,25 @@ Xiaojuan Tan and Jelke Bloem
 15:15-16:30: discussion/data session
 
 
+### Invited speakers
+
+#### [Maria Antoniak](https://maria-antoniak.github.io/)
+
+Title: tba
+
+
+
+#### [Vered Shwartz](https://www.cs.ubc.ca/~vshwartz/)
+
+Title: **It's not what you said, it's how you said it: Reference, Framing, and Perspective**
+
+Abstract:
+
+Lexical variability, i.e. the ability to express the same meaning in various surface forms, poses multiple challenges for NLP applications, even in the age of LLMs. First, models need to respond consistently to queries regardless of their phrasing, which they still struggle to do. Second, resolving co-references to the same real-world events and entities is not trivial when it requires reading between the lines and making inferences. Third, people from diverse cultural backgrounds may differ in their lexical choices; for example, describing events with a focus on either the agent or the contextual factors; and their interpretation of references, such as which hours count as “morning” and which shades count as “blue”. LLMs, which are predominantly trained on English text from US-based users, “understand” the world through a narrow Western or North American lens. Finally, speakers often choose wording that serves their agenda or signals their belonging to a certain group. People’s lexical choice and differences in framing can be used to identify their opinions even when they are not explicit. LLMs’ lexical choice is increasingly controlled by the developers to avoid generating harmful content, which may eventually change the way we speak.
+
+*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, multimodal models, 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.*
+
+
 ## Call for Papers
 
 When something happens in the world, we have access to an unlimited range of ways (from lexical choices to specific syntactic structures) to refer to the same real-world event. We can chose to express information explicitly or imply it. Variations in reference may convey radically different perspectives. This process of making reference to something by adopting a specific perspective is also known as framing. Although previous work in this area is present (see Ali and Hassan (2022)’s survey for an overview), there is a lack of a unitary framework and only few targeted datasets (Chen et al., 2019) and tools based on Large Language Models exist (Minnema et al., 2022). In this workshop, we propose to adopt Frame Semantics (Fillmore, 1968, 1985, 2006)  as a unifying theoretical framework and analysis method to understand the choices made in linguistic references to events. The semantic frames (expressed by predicates and roles) we choose give rise to our understanding, or framing, of an event. We aim to bring together different research communities interested in lexical and syntactic variation, referential grounding, frame semantics, and perspectives. We believe that there is significant overlap within the goals and interests of these communities, but not necessarily the common ground to enable collaborative work.
@@ -87,11 +106,7 @@ Please submit your contribution via this link: [Submission link](https://softcon
 You can select the appropriate paper category (long paper, short paper, extended abstract)
 
 
-### Invited speakers
-
-[Maria Antoniak](https://maria-antoniak.github.io/)
 
-[Vered Shwartz](https://www.cs.ubc.ca/~vshwartz/)
 
 ### Organizers