2 citations · 3 across the 9 of their papers we have counts for
11 papers
Kwai Summary Attention V2 Technical Report
OneRec Team, Chenglong Chu, Guohong Mu +30
Summary-token architectures such as Kwai Summary Attention (KSA) compress distant context into learnable Summary token per chunk, and hybrid variants interleave these layers with f…
KUAISHOU Explorer LLM-Rec Challenge 2026: Reasoning Generative Recommendation
Jiangxia Cao, Hao Peng, Wenlong Xu +97
Generative recommendation, has been attracted a surge of attentions in industrial and academic research community, towards to build more smart system to build next-generation recom…
Recovering General Capabilities via Uncertainty-Calibrated Multi-Teacher On-Policy Distillation
Ziyuan Liu, Jiao Ou, Jian Liang +2
Specializing large language models to vertical domains improves domain-specific behavior but often degrades general capabilities. We study this trade-off in Multi-Teacher On-Policy…
OneReason Technical Report
OneRec Team, Biao Yang, Boyang Ding +81
Generative recommendation models in the OneRec family have been widely deployed in many real-world services, such as short-video, live-streaming, advertising, and e-commerce. Howev…
Counteraction-Aware Multi-Teacher On-Policy Distillation for General Capability Recovery with Domain Preservation
Tianlei Chen, Jiao Ou, Ziyuan Liu +3
Domain specialization can improve LLM behavior, but often weakens the general capabilities inherited from the original model. Recent Multi-Teacher On-Policy Distillation (MOPD) pip…
Kwai Summary Attention Technical Report
Chenglong Chu, Guorui Zhou, Guowang Zhang +35
Long-context ability, has become one of the most important iteration direction of next-generation Large Language Models, particularly in semantic understanding/reasoning, code agen…
FlexDuo: A Pluggable System for Enabling Full-Duplex Capabilities in Speech Dialogue Systems
Borui Liao, Yulong Xu, Jiao Ou +4
Full-Duplex Speech Dialogue Systems (Full-Duplex SDS) have significantly enhanced the naturalness of human-machine interaction by enabling real-time bidirectional communication. Ho…
ERABAL: Enhancing Role-Playing Agents through Boundary-Aware Learning
Yihong Tang, Jiao Ou, Che Liu +3
Role-playing is an emerging application in the field of Human-Computer Interaction (HCI), primarily implemented through the alignment training of a large language model (LLM) with…
Inductive-Deductive Strategy Reuse for Multi-Turn Instructional Dialogues
Jiao Ou, Jiayu Wu, Che Liu +3
Aligning large language models (LLMs) with human expectations requires high-quality instructional dialogues, which usually require instructions that are diverse and in-depth. Exist…
Enhancing Role-playing Systems through Aggressive Queries: Evaluation and Improvement
Yihong Tang, Jiao Ou, Che Liu +3
The advent of Large Language Models (LLMs) has propelled dialogue generation into new realms, particularly in the field of role-playing systems (RPSs). While enhanced with ordinary…
DialogBench: Evaluating LLMs as Human-like Dialogue Systems
Jiao Ou, Junda Lu, Che Liu +4
Large language models (LLMs) have achieved remarkable breakthroughs in new dialogue capabilities by leveraging instruction tuning, which refreshes human impressions of dialogue sys…