Papers
176,624 papers found
Diversification Catalyzes Language Models’ Instruction Generalization To Unseen Semantics
Dylan Zhang, Justin Wang, Francois Charton
Diversifying Query: Region-Guided Transformer for Temporal Sentence Grounding
Xiaolong Sun, Liushuai Shi, Le Wang et al.
Diversifying the Expert Knowledge for Task-Agnostic Pruning in Sparse Mixture-of-Experts
Zeliang Zhang, Xiaodong Liu, Hao Cheng et al.
Diversify-verify-adapt: Efficient and Robust Retrieval-Augmented Ambiguous Question Answering
Yeonjun In, Sungchul Kim, Ryan A. Rossi et al.
Diversity-Aware Reinforcement Learning for de novo Drug Design
Hampus Gummesson Svensson, Christian Tyrchan, Ola Engkvist et al.
Diversity-Enhanced Distribution Alignment for Dataset Distillation
Hongcheng Li, Yucan Zhou, Xiaoyan Gu et al.
Diversity Explains Inference Scaling Laws: Through a Case Study of Minimum Bayes Risk Decoding
Hidetaka Kamigaito, Hiroyuki Deguchi, Yusuke Sakai et al.
Diversity Helps Jailbreak Large Language Models
Weiliang Zhao, Daniel Ben-Levi, Wei Hao et al.
Diversity-oriented Data Augmentation with Large Language Models
Zaitian Wang, Jinghan Zhang, Xinhao Zhang et al.
DIVE: Taming DINO for Subject-Driven Video Editing
Yi Huang, Wei Xiong, He Zhang et al.
DIV-FF: Dynamic Image-Video Feature Fields For Environment Understanding in Egocentric Videos
Lorenzo Mur-Labadia, Josechu Guerrero, Ruben Martinez-Cantin
DivGCL: A Graph Contrastive Learning Model for Diverse Recommendation
Wenwen Gong, Yangliao Geng, Dan Zhang et al.
Divide and Conquer: Coordinating Multiplex Mixture of Graph Learners to Handle Multi-Omics Analysis
Zhihao Wu, Jielong Lu, Jiajun Yu et al.
Divide-and-Conquer for Enhancing Unlabeled Learning, Stability, and Plasticity in Semi-supervised Continual Learning
Yue Duan, Taicai Chen, Lei Qi et al.
Divide and Conquer: Heterogeneous Noise Integration for Diffusion-based Adversarial Purification
Gaozheng Pei, Shaojie Lyu, Gong Chen et al.
Divide-and-Conquer: Tree-structured Strategy with Answer Distribution Estimator for Goal-Oriented Visual Dialogue
Shuo Cai, Xinzhe Han, Shuhui Wang
Divide, Conquer and Combine: A Training-Free Framework for High-Resolution Image Perception in Multimodal Large Language Models
Wenbin Wang, Liang Ding, Minyan Zeng et al.
Divide, Link, and Conquer: Recall-oriented Schema Linking for NL-to-SQL via Question Decomposition
Kiran Pradeep, Kirushikesh Db, Nishtha Madaan et al.
Divide, Optimize, Merge: Scalable Fine-Grained Generative Optimization for LLM Agents
Jiale Liu, Yifan Zeng, Shaokun Zhang et al.
Divide-Solve-Combine: An Interpretable and Accurate Prompting Framework for Zero-shot Multi-Intent Detection
Libo Qin, Qiguang Chen, Jingxuan Zhou et al.
Divide-Then-Aggregate: An Efficient Tool Learning Method via Parallel Tool Invocation
Dongsheng Zhu, Weixian Shi, Zhengliang Shi et al.
Divide-Then-Align: Honest Alignment based on the Knowledge Boundary of RAG
Xin Sun, Jianan Xie, Zhongqi Chen et al.
Divide-Verify-Refine: Can LLMs Self-align with Complex Instructions?
Xianren Zhang, Xianfeng Tang, Hui Liu et al.
Dividing Conflicting Items Fairly
Ayumi Igarashi, Pasin Manurangsi, Hirotaka Yoneda
Diving into Mitigating Hallucinations from a Vision Perspective for Large Vision-Language Models
Weihang Wang, Xinhao Li, Ziyue Wang et al.