Tiago Ribeiro

Stephanie Brandl, Oliver Eberle, Tiago Ribeiro et al.

Rationales in the form of manually annotated input spans usually serve as ground truth when evaluating explainability methods in NLP. They are, however, time-consuming and often biased by the annotation process. In this paper, we debate whether human gaze, in the form of webcam-based eye-tracking recordings, poses a valid alternative when evaluating importance scores. We evaluate the additional information provided by gaze data, such as total reading times, gaze entropy, and decoding accuracy with respect to human rationale annotations. We compare WebQAmGaze, a multilingual dataset for information-seeking QA, with attention and explainability-based importance scores for 4 different multilingual Transformer-based language models (mBERT, distil-mBERT, XLMR, and XLMR-L) and 3 languages (English, Spanish, and German). Our pipeline can easily be applied to other tasks and languages. Our findings suggest that gaze data offers valuable linguistic insights that could be leveraged to infer task difficulty and further show a comparable ranking of explainability methods to that of human rationales.

Tiago Ribeiro, Ana Paiva

Robot animation is a new form of character animation that extends the traditional process by allowing the animated motion to become more interactive and adaptable during interaction with users in real-world settings. This paper reviews how this new type of character animation has evolved and been shaped from character animation principles and practices. We outline some new paradigms that aim at allowing character animators to become robot animators, and to properly take part in the development of social robots. One such paradigm consists of the 12 principles of robot animation, which describes general concepts that both animators and robot developers should consider in order to properly understand each other. We also introduce the concept of Kinematronics, for specifying the controllable and programmable expressive abilities of robots, and the Nutty Workflow and Pipeline. The Nutty Pipeline introduces the concept of the Programmable Robot Animation Engine, which allows to generate, compose and blend various types of animation sources into a final, interaction-enabled motion that can be rendered on robots in real-time during real-world interactions. The Nutty Motion Filter is described and exemplified as a technique that allows an open-loop motion controller to apply physical limits to the motion while still allowing to tweak the shape and expressivity of the resulting motion. Additionally, we describe some types of tools that can be developed and integrated into Nutty-based workflows and pipelines, which allow animation artists to perform an integral part of the expressive behaviour development within social robots, and thus to evolve from standard (3D) character animators, towards a full-stack type of robot animators.