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cs.CL2026
Same Semantics, Different Outcome: On the Modality Robustness of Multimodal LLMs under Knowledge Conflict
Jungyeon Lee, Yejin Yoon, Taeuk Kim
Multimodal large language models (MLLMs) are increasingly provided with contextual evidence in heterogeneous forms: as a text passage, as a rendered image of the same passage, or a…
cs.CL2026
Latent Preference Modeling for Multi-Session Personalized Tool Calling
Yejin Yoon, Minseo Kim, Taeuk Kim
Users often omit essential details in their requests to LLM-based agents, resulting in under-specified inputs for tool use. This poses a fundamental challenge for tool-augmented ag…