FBK's Long-form SpeechLLMs for IWSLT 2026 Instruction Following
Zhihang Xie, Marco Gaido, Sara Papi, Matteo Negri, Luisa Bentivogli
Abstract
This paper describes our submission to the IWSLT 2026 Instruction Following shared task. SpeechLLMs are developed for both short-form and long-form speech instruction following under constrained settings. For the short track, strong performance is achieved on MCIF, with a SIFS score of 2.0708. For the long track, three speech segmentation methods are explored, and the HIFS score is introduced to account for unstable long-form generation. Experimental results show that fixed 30-second segmentation provides the most robust long-form performance, achieving the highest HIFS score of 2.0663. Further analysis shows that hallucination mainly manifests as repetitive insertions in generated outputs, substantially affecting ASR and SSUM, while short-form capabilities are largely retained after long-form extension.
Topics
Classified with taxonomy v2 on Wed, 2 Sept 2026.