3 accepted papers
Autoregressive language models frequently degrade during long-horizon generation, producing repetitive text, losing instruction adherence, and exhibiting unstable entropy. Despite the prevalence of these failures, practitioners lack online diagnostics to detect them in real time as they occur. We fo…
Societal biases present in pre-trained large language models are a critical issue as these models have been shown to propagate biases in countless downstream applications, rendering them unfair towards specific groups of people. Since large-scale retraining of these models from scratch is both time…
Visual question answering (VQA) lies at the intersection of language and vision research. It functions as a building block for multimodal conversational AI and serves as a testbed for assessing a model’s capability for open-domain scene understanding. While progress in this area was initially accele…