Zobrazeno 1 - 10
of 143
pro vyhledávání: '"Yang, Tianchi"'
Autor:
Liu, Yuxuan, Yang, Tianchi, Zhang, Zihan, Song, Minghui, Huang, Haizhen, Deng, Weiwei, Sun, Feng, Zhang, Qi
Generative retrieval, a promising new paradigm in information retrieval, employs a seq2seq model to encode document features into parameters and decode relevant document identifiers (IDs) based on search queries. Existing generative retrieval solutio
Externí odkaz:
http://arxiv.org/abs/2405.14280
Autor:
Ma, Jie, Yang, Tianchi
In this paper, we investigate the hypergraph Tur\'an number $ex(n,K^{(r)}_{s,t})$. Here, $K^{(r)}_{s,t}$ denotes the $r$-uniform hypergraph with vertex set $\left(\cup_{i\in [t]}X_i\right)\cup Y$ and edge set $\{X_i\cup \{y\}: i\in [t], y\in Y\}$, wh
Externí odkaz:
http://arxiv.org/abs/2403.04318
With the great popularity of Graph Neural Networks (GNNs), their robustness to adversarial topology attacks has received significant attention. Although many attack methods have been proposed, they mainly focus on fixed-budget attacks, aiming at find
Externí odkaz:
http://arxiv.org/abs/2403.02723
Autor:
Liu, Yuxuan, Yang, Tianchi, Huang, Shaohan, Zhang, Zihan, Huang, Haizhen, Wei, Furu, Deng, Weiwei, Sun, Feng, Zhang, Qi
Large language models (LLMs) have emerged as a promising alternative to expensive human evaluations. However, the alignment and coverage of LLM-based evaluations are often limited by the scope and potential bias of the evaluation prompts and criteria
Externí odkaz:
http://arxiv.org/abs/2402.15754
Autor:
Liu, Yuxuan, Yang, Tianchi, Huang, Shaohan, Zhang, Zihan, Huang, Haizhen, Wei, Furu, Deng, Weiwei, Sun, Feng, Zhang, Qi
Diffusion models have demonstrated exceptional capability in generating high-quality images, videos, and audio. Due to their adaptiveness in iterative refinement, they provide a strong potential for achieving better non-autoregressive sequence genera
Externí odkaz:
http://arxiv.org/abs/2402.14843
Autor:
Yang, Tianchi, Song, Minghui, Zhang, Zihan, Huang, Haizhen, Deng, Weiwei, Sun, Feng, Zhang, Qi
Generative retrieval, which is a new advanced paradigm for document retrieval, has recently attracted research interests, since it encodes all documents into the model and directly generates the retrieved documents. However, its power is still underu
Externí odkaz:
http://arxiv.org/abs/2310.12455
Autor:
Liu, Yuxuan, Yang, Tianchi, Huang, Shaohan, Zhang, Zihan, Huang, Haizhen, Wei, Furu, Deng, Weiwei, Sun, Feng, Zhang, Qi
Recent advancements in large language models (LLMs) on language modeling and emergent capabilities make them a promising reference-free evaluator of natural language generation quality, and a competent alternative to human evaluation. However, hinder
Externí odkaz:
http://arxiv.org/abs/2309.13308
A graph is called $k$-critical if its chromatic number is $k$ but any proper subgraph has chromatic number less than $k$. An old and important problem in graph theory asks to determine the maximum number of edges in an $n$-vertex $k$-critical graph.
Externí odkaz:
http://arxiv.org/abs/2301.01656
Autor:
Ma, Jie, Yang, Tianchi
For a family $\mathcal{F}$ of graphs, let $ex(n,\mathcal{F})$ denote the maximum number of edges in an $n$-vertex graph which contains none of the members of $\mathcal{F}$ as a subgraph. A longstanding problem in extremal graph theory asks to determi
Externí odkaz:
http://arxiv.org/abs/2112.13689
Publikováno v:
In Vaccine 13 August 2024 42(20)
