Beyond Log Likelihood: Probability-Based Objectives for Supervised Fine-Tuning across the Model Capability Continuum
Gaotang Li · Ruizhong Qiu · Xiusi Chen · Heng Ji · Hanghang Tong
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Gaotang Li · Ruizhong Qiu · Xiusi Chen · Heng Ji · Hanghang Tong
Yupeng Hou · Jiacheng Li · Xiangjun Fu · Zhankui He · An Yan · Xiusi Chen · Julian J. McAuley
Feature engineering has long been central to recommender systems, yet effectively leveraging textual item features remains challenging. Recent advances in large language models (LLMs) have enabled their use as semantic encoders for recommendation, but their roles and behaviors in this setting are...
Cheng Qian · Emre Can Acikgoz · Bingxuan Li · Xiusi Chen · Yuji Zhang · Bingxiang He · Qinyu Luo · Gokhan Tur · Dilek Hakkani-Tür · Yunzhu Li · Heng Ji
Agents built on vision-language models increasingly face tasks that demand anticipating future states rather than relying on short-horizon reasoning. Generative world models offer a promising remedy: agents could use them as external simulators to foresee outcomes before acting. This paper empiri...
Bingxuan Li · Jeonghwan Kim · Cheng Qian · Xiusi Chen · Eitan Anzenberg · Niran Kundapur · Heng Ji
Overlapping calendar invitations force busy professionals to repeatedly decide which meetings to attend, reschedule, or decline. We refer to this preference-driven decision process as calendar conflict resolution. Automating this decision process is crucial yet challenging. Scheduling logistics c...
Qi He · Cheng Qian · Xiusi Chen · Bingxiang He · Yi R. Fung · Heng Ji
Claim verification with large language models (LLMs) has recently attracted growing attention, due to their strong reasoning capabilities and transparent verification processes compared to traditional answer-only judgments. However, existing approaches to online claim verification, which requires...