3 papers
cs.LG2025
What's in Common? Multimodal Models Hallucinate When Reasoning Across Scenes
Candace Ross, Florian Bordes, Adina Williams +2
Multimodal language models possess a remarkable ability to handle an open-vocabulary's worth of objects. Yet the best models still suffer from hallucinations when reasoning about s…
cs.CL2025
LLM Knowledge is Brittle: Truthfulness Representations Rely on Superficial Resemblance
Patrick Haller, Mark Ibrahim, Polina Kirichenko +2
For Large Language Models (LLMs) to be reliable, they must learn robust knowledge that can be generally applied in diverse settings -- often unlike those seen during training. Yet,…
cs.AI2025
AbstentionBench: Reasoning LLMs Fail on Unanswerable Questions
Polina Kirichenko, Mark Ibrahim, Kamalika Chaudhuri +1
For Large Language Models (LLMs) to be reliably deployed in both everyday and high-stakes domains, knowing when not to answer is equally critical as answering correctly. Real-world…