From the 2 of 12 linked papers with an AI index.
12 papers
Target-Aware Calibration Data Selection for Preserving Uncertainty in Quantized Language Models
Zhen Yang, Sizai Hou, Kaiwen Zheng +4
Quantization is widely used to deploy large language models, but its effect on uncertainty behavior, such as confidence, margins, and abstention, is rarely treated as a primary obj…
RecRec: Latent Interests Recursive Reasoning for Sequential Recommendation
Wenhao Deng, Junchen Fu, Hanwen Du +6
The paper introduces RecRec, a framework that separates reasoning from prediction in sequential recommendation by compressing user histories into multiple latent interests and recu…
Do We Really Need Multimodal Emotion Language Models Larger Than 1B Parameters?
Kaiwen Zheng, Junchen Fu, Wenhao Deng +3
The paper introduces Light-MER, a sub‑billion‑parameter multimodal emotion recognition model that uses knowledge distillation, an optimal transport loss, and a multi‑reward optimiz…
Stream-aware Side Adaptation for Large Pre-trained Multimodal Embedding Models in Sequential Recommendation
Junchen Fu, Kaiwen Zheng, Ioannis Arapakis +4
Recently, large pretrained multimodal embedding models such as Qwen3-VL Embedding have shown strong promise for sequential recommendation, as they provide reusable semantic item re…
Training-Free Test-Time Contrastive Learning for Large Language Models
Kaiwen Zheng, Kai Zhou, Jinwu Hu +3
Large language models (LLMs) demonstrate strong reasoning capabilities, but their performance often degrades under distribution shift. Existing test-time adaptation (TTA) methods r…
Benchmarking Multimodal Large Language Models for Missing Modality Completion in Product Catalogues
Junchen Fu, Wenhao Deng, Kaiwen Zheng +5
Missing-modality information on e-commerce platforms, such as absent product images or textual descriptions, often arises from annotation errors or incomplete metadata, impairing b…