3 papers
cs.AI2026
Mitigating Cross-Modal Hallucinations by Correcting Modality Misrouting in Omnimodal LLMs
Yu Mi, Licheng Pan, Jiayi Zhu +7
Omnimodal large language models (OLLMs) are susceptible to cross-modal hallucinations under audio-visual interference. We find that, for a substantial fraction of incorrect joint p…
cs.IR2026
Fighting Numerical Hallucinations via Data-centric Compilation for Online Financial QA
Hao Chen, Xing Tang, Qirui Liu +6
Large Language Models (LLMs) have significantly advanced online data services, particularly in the domain of financial question answering (FinQA). However, such systems remain susc…
cs.LG2026
Cognitive-Uncertainty Guided Knowledge Distillation for Accurate Classification of Student Misconceptions
Qirui Liu, Hao Chen, Weijie Shi +2
Accurately identifying student misconceptions is crucial for personalized education but faces three challenges: (1) data scarcity with long-tail distribution, where authentic stude…