4 papers
Diagnosing the Sources of Compositional Failure in Vision-Language Models: A Controlled Analysis
Mona Gandhi, Cenk Merih Olcay, Kuan-Chieh Lo +3
Vision-language models (VLMs) often struggle with compositional reasoning tasks, but the reasons for this underperformance remain unclear. A common hypothesis is that models strugg…
Temporal Taxation Compounds Under Post-Training Compression of Whisper Models
Srishti Ginjala, Eric Fosler-Lussier, Christopher W. Myers +1
Automatic speech recognition models are audited for demographic fairness at full precision, yet the models that ship to production have been quantized, pruned, and distilled. We as…
Do LLM Decoders Listen Fairly? Benchmarking How Language Model Priors Shape Bias in Speech Recognition
Srishti Ginjala, Eric Fosler-Lussier, Christopher W. Myers +1
As pretrained large language models replace task-specific decoders in speech recognition, a critical question arises: do their text-derived priors make recognition fairer or more b…
Understanding Knowledge Gaps in Visual Question Answering: Implications for Gap Identification and Testing
Goonmeet Bajaj, Bortik Bandyopadhyay, Daniel Schmidt +3
Visual Question Answering (VQA) systems are tasked with answering natural language questions corresponding to a presented image. Traditional VQA datasets typically contain question…