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Measuring the Redundancy of Decoder Layers in SpeechLLMs
Adel Moumen, Guangzhi Sun, Philip C Woodland
Speech Large Language Models route speech encoder representations into an LLM decoder that typically accounts for over 90% of total parameters. We study how much of this decoder ca…
Cross-Lingual Interleaving for Speech Language Models
Adel Moumen, Guangzhi Sun, Philip C. Woodland
Spoken Language Models (SLMs) aim to learn linguistic competence directly from speech using discrete units, widening access to Natural Language Processing (NLP) technologies for la…
CASE-Bench: Context-Aware SafEty Benchmark for Large Language Models
Guangzhi Sun, Xiao Zhan, Shutong Feng +2
Aligning large language models (LLMs) with human values is essential for their safe deployment and widespread adoption. Current LLM safety benchmarks often focus solely on the refu…
SkillAggregation: Reference-free LLM-Dependent Aggregation
Guangzhi Sun, Anmol Kagrecha, Potsawee Manakul +2
Large Language Models (LLMs) are increasingly used to assess NLP tasks due to their ability to generate human-like judgments. Single LLMs were used initially, however, recent work…