13 papers
Distill on a Diet: Efficient Knowledge Distillation via Learnable Data Pruning
Yifan Wu, Yiqi Wang, Xichen Ye +5
Knowledge Distillation (KD) is widely used to obtain compact models for efficient inference in resource-constrained environments. Yet the computational overhead of the distillation…
BlossomRec: Block-level Fused Sparse Attention Mechanism for Sequential Recommendations
Mengyang Ma, Xiaopeng Li, Wanyu Wang +9
Transformer structures have been widely used in sequential recommender systems (SRS). However, as user interaction histories increase, computational time and memory requirements al…
SEARCH-R: Structured Entity-Aware Retrieval with Chain-of-Reasoning Navigator for Multi-hop Question Answering
Yuqing Fu, Yimin Deng, Wanyu Wang +9
Multi-hop Question Answering (MHQA) aims to answer questions that require multi-step reasoning. It presents two key challenges: generating correct reasoning paths in response to th…
Diffusion Generative Recommendation with Continuous Tokens
Haohao Qu, Shanru Lin, Yujuan Ding +2
Recent advances in generative artificial intelligence, particularly large language models (LLMs), have opened new opportunities for enhancing recommender systems (RecSys). Most exi…
Cognitive Chunking for Soft Prompts: Accelerating Compressor Learning via Block-wise Causal Masking
Guojie Liu, Yiqi Wang, Yanfeng Yang +4
Providing extensive context via prompting is vital for leveraging the capabilities of Large Language Models (LLMs). However, lengthy contexts significantly increase inference laten…
Investigating Data Pruning for Pretraining Biological Foundation Models at Scale
Yifan Wu, Jiyue Jiang, Xichen Ye +9
Biological foundation models (BioFMs), pretrained on large-scale biological sequences, have recently shown strong potential in providing meaningful representations for diverse down…