ZS-CIR aims to retrieve a target image from a reference image and a modification text without paired supervision, typically by encoding composed queries as text-dominant representations within the image-text matching space of VLPs. However, queries reconstructed by visual pseudo-word learning or MLLM-based target reaso...
Xuri Ge, Chun-Hao Wang, Junchen Fu et al.· 0 citations
Large language models (LLMs) are increasingly used for information seeking, where users find, compare, and evaluate information through dialogue. In this role, the assistant does more than retrieve or generate content: it shapes how users articulate constraints, ask follow-up questions, verify claims, and decide when a...
Abdisalam Abukar, Junchen Fu, Cheng-Li Zhai et al.· 0 citations
Generative retrieval (GR) enables end-to-end retrieval by generating document semantic identifiers (SIDs). However, retrieval-only fine-tuning can over-specialize pretrained language models to SID prediction, substantially distorting their natural-language distribution and limiting their suitability for interactive sys...
Junchen Fu, Kleomenis Katevas, Vandana Rajan et al.· 0 citations
Video generation is central to AI-powered content creation. Aligning generated videos with human preferences is a key criterion for evaluating generation quality. Despite significant progress in visual quality, three key challenges remain. First, the reliability of reward signals is constrained by the quality of human...
Nai-Xin Zhai, Weihua Cheng, De-Xu Yu et al.· 0 citations
Experiments on five real-world datasets show that \textsc{DS-Frame} consistently improves representative sequential recommendation backbones, with larger gains on challenging groups and effective accuracy--efficiency trade-offs, highlighting the potential of adaptive inference for more efficient and robust recommendati...
Zi-Chen Yuan, Xiao-Xuan Dong, Linkun Dai et al.· 0 citations
This survey reviews core tasks, representative methods, and datasets in multimodal facial state analysis, focusing on facial expression recognition, AU detection, and face-based soft biometric estimation, and emphasizing the unique value of language in providing contextual semantics, enhancing reasoning, and generating...
Xuri Ge, Tian-Shuo Zhang, Ruihan Li et al.· 0 citations
It is indicated that retrieval-stage filtering can reduce the candidate action space exposed to agents before execution, complementing downstream tool-use safeguards, and providing a conservative operating point for safety-critical deployments.
Qinfei Li, Xiaoxuan Dong, Jin Zhang et al.· 2 citations
Rec is proposed, an RL-free framework that decouples reasoning from prediction, overcoming the fixed d-dimensional state bottleneck of prior methods, and points to a decoupled, multi-vector recipe that unleashes latent reasoning from the single-state bottleneck of prior methods.
Wenhao Deng, Junchen Fu, Han-Wen Du et al.· arXiv.org· 0 citations
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