12 papers
LifeSide: Benchmarking Agents as Lifelong Digital Companions
Yuqian Wu, Zhijie Deng, Wei Chen +8
Lifelong digital companions must integrate cross-session cues, continually update their understanding of users, and adapt to shifting privacy boundaries. Existing evaluations fail…
Calibrated Multimodal Representation Learning with Missing Modalities
Xiaohao Liu, Xiaobo Xia, Jiaheng Wei +4
Multimodal representation learning harmonizes distinct modalities by aligning them into a unified latent space. Recent research generalizes traditional cross-modal alignment to pro…
IDEA: An Interpretable and Editable Decision-Making Framework for LLMs via Verbal-to-Numeric Calibration
Yanji He, Yuxin Jiang, Yiwen Wu +3
Large Language Models are increasingly deployed for decision-making, yet their adoption in high-stakes domains remains limited by miscalibrated probabilities, unfaithful explanatio…
Robust Preference Alignment via Directional Neighborhood Consensus
Ruochen Mao, Yuling Shi, Xiaodong Gu +1
Aligning large language models with human preferences is critical for creating reliable and controllable AI systems. A human preference can be visualized as a high-dimensional vect…
OFFSIDE: Benchmarking Unlearning Misinformation in Multimodal Large Language Models
Hao Zheng, Zirui Pang, Ling li +5
Advances in Multimodal Large Language Models (MLLMs) intensify concerns about data privacy, making Machine Unlearning (MU), the selective removal of learned information, a critical…
ENTP: Enhancing Low-Quality SFT Data via Neural-Symbolic Text Purge-Mix
Zile Yang, Ling Li, Na Di +5
Supervised Fine-Tuning (SFT) adapts pre-trained Large Language Models (LLMs) to domain-specific instructions by training on a carefully curated subset of high-quality instruction-r…