6 papers
GenRec: A Preference-Oriented Generative Framework for Large-Scale Recommendation
Yanyan Zou, Junbo Qi, Lunsong Huang +7
Generative Retrieval (GR) offers a promising paradigm for recommendation through next-token prediction (NTP). However, scaling it to large-scale industrial systems introduces three…
Seedance 2.0: Advancing Video Generation for World Complexity
Team Seedance, De Chen, Liyang Chen +168
Seedance 2.0 is a new native multi-modal audio-video generation model, officially released in China in early February 2026. Compared with its predecessors, Seedance 1.0 and 1.5 Pro…
LLM as Attention-Informed NTM and Topic Modeling as long-input Generation: Interpretability and long-Context Capability
Xuan Xu, Zhongliang Yang, Haolun Li +5
Topic modeling aims to produce interpretable topic representations and topic--document correspondences from corpora, but classical neural topic models (NTMs) remain constrained by…
Dynamic Summary Generation for Interpretable Multimodal Depression Detection
Shiyu Teng, Jiaqing Liu, Hao Sun +6
Depression remains widely underdiagnosed and undertreated because stigma and subjective symptom ratings hinder reliable screening. To address this challenge, we propose a coarse-to…
FinCPRG: A Bidirectional Generation Pipeline for Hierarchical Queries and Rich Relevance in Financial Chinese Passage Retrieval
Xuan Xu, Beilin Chu, Qinhong Lin +7
In recent years, large language models (LLMs) have demonstrated significant potential in constructing passage retrieval datasets. However, existing methods still face limitations i…
FinBERT2: A Specialized Bidirectional Encoder for Bridging the Gap in Finance-Specific Deployment of Large Language Models
Xuan Xu, Fufang Wen, Beilin Chu +7
In natural language processing (NLP), the focus has shifted from encoder-only tiny language models like BERT to decoder-only large language models(LLMs) such as GPT-3. However, LLM…