From the 1 of 12 linked papers with an AI index.
12 papers
From Reasoning Depth to Reasoning Breadth: Evaluating Multi-Point Associative Reasoning in Large Language Models
Si'an Xie, Jiaxun Liu, Biao Yang +4
Large language models (LLMs) have made substantial progress on reasoning tasks that require increasingly long and complex inferential chains. This progress primarily reflects reaso…
PushDualGen: Enabling LLMs to Generate Semantic IDs with Interpretable Copy for Industrial Push Recommendation
Manjia Lin, Da Li, Yan Wang +9
Push recommendation in KuaiShou proactively delivers personalized content to nearly one billion users to facilitate their engagement. Recently, generative recommendation has achiev…
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding?
Yun Li, Biao Yang, Peixi Wu +5
Embeddings have emerged as a standard representational interface linking foundation models with downstream systems. Most embedding benchmarks assess representations through discrim…
LaME: Learning to Think in Latent Space for Multimodal Embedding via Information Bottleneck
Peixi Wu, Biao Yang, Feipeng Ma +7
The paper introduces LaME, a multimodal embedding model that performs reasoning in a compact latent space using learnable tokens and an information‑bottleneck objective, eliminatin…
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…
Compressing then Matching: An Efficient Pre-training Paradigm for Multimodal Embedding
Da Li, Yuxiao Luo, Keping Bi +7
Multimodal Large Language Models advance multimodal representation learning by acquiring transferable semantic embeddings, thereby substantially enhancing performance across a rang…