Sebastian Löbbers

John Dougrez-Lewis, Mahmud Elahi Akhter, Federico Ruggeri et al.

Although LLMs have shown great performance on Mathematics and Coding related reasoning tasks, the reasoning capabilities of LLMs regarding other forms of reasoning are still an open problem. Here, we examine the issue of reasoning from the perspective of claim verification. We propose a framework designed to break down any claim paired with evidence into atomic reasoning types that are necessary for verification. We use this framework to create RECV, the first claim verification benchmark, incorporating real-world claims, to assess the deductive and abductive reasoning capabilities of LLMs. The benchmark comprises of three datasets, covering reasoning problems of increasing complexity. We evaluate three state-of-the-art proprietary LLMs under multiple prompt settings. Our results show that while LLMs can address deductive reasoning problems, they consistently fail in cases of abductive reasoning. Moreover, we observe that enhancing LLMs with rationale generation is not always beneficial. Nonetheless, we find that generated rationales are semantically similar to those provided by humans, especially in deductive reasoning cases.

Sebastian Löbbers, Mathieu Barthet, György Fazekas

Sound synthesiser controls typically correspond to technical parameters of signal processing algorithms rather than intuitive sound descriptors that relate to human perception of sound. This makes it difficult to realise sound ideas in a straightforward way. Cross-modal mappings, for example between gestures and sound, have been suggested as a more intuitive control mechanism. A large body of research shows consistency in human associations between sounds and shapes. However, the use of drawings to drive sound synthesis has not been explored to its full extent. This paper presents an exploratory study that asked participants to sketch visual imagery of sounds with a monochromatic digital drawing interface, with the aim to identify different representational approaches and determine whether timbral sound characteristics can be communicated reliably through visual sketches. Results imply that the development of a synthesiser exploiting sound-shape associations is feasible, but a larger and more focused dataset is needed in followup studies.