Search Results for author: Xiaoyuan Yi

Found 33 papers, 13 papers with code

CLAVE: An Adaptive Framework for Evaluating Values of LLM Generated Responses

no code implementations15 Jul 2024 Jing Yao, Xiaoyuan Yi, Xing Xie

The rapid progress in Large Language Models (LLMs) poses potential risks such as generating unethical content.

Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing

no code implementations20 Jun 2024 Han Jiang, Xiaoyuan Yi, Zhihua Wei, Shu Wang, Xing Xie

Distinct from previous adaptive testing methods that rely on static datasets with limited difficulty, GETA incorporates an iteratively-updated item generator which infers each LLM's moral boundaries and generates difficulty-tailored testing items, accurately reflecting the true alignment extent.

Ethics

Multi-Evidence based Fact Verification via A Confidential Graph Neural Network

1 code implementation17 May 2024 Yuqing Lan, Zhenghao Liu, Yu Gu, Xiaoyuan Yi, Xiaohua LI, Liner Yang, Ge Yu

Nevertheless, the noisy nodes usually propagate their semantics via the edges of the reasoning graph, which misleads the semantic representations of other nodes and amplifies the noise signals.

Fact Verification Graph Attention +1

Beyond Human Norms: Unveiling Unique Values of Large Language Models through Interdisciplinary Approaches

no code implementations19 Apr 2024 Pablo Biedma, Xiaoyuan Yi, Linus Huang, Maosong Sun, Xing Xie

Recent advancements in Large Language Models (LLMs) have revolutionized the AI field but also pose potential safety and ethical risks.

Negating Negatives: Alignment without Human Positive Samples via Distributional Dispreference Optimization

1 code implementation6 Mar 2024 Shitong Duan, Xiaoyuan Yi, Peng Zhang, Tun Lu, Xing Xie, Ning Gu

Large language models (LLMs) have revolutionized the role of AI, yet also pose potential risks of propagating unethical content.

ToolNet: Connecting Large Language Models with Massive Tools via Tool Graph

no code implementations29 Feb 2024 Xukun Liu, Zhiyuan Peng, Xiaoyuan Yi, Xing Xie, Lirong Xiang, Yuchen Liu, Dongkuan Xu

While achieving remarkable progress in a broad range of tasks, large language models (LLMs) remain significantly limited in properly using massive external tools.

In-Context Learning

LegalDuet: Learning Effective Representations for Legal Judgment Prediction through a Dual-View Legal Clue Reasoning

no code implementations27 Jan 2024 Pengjie Liu, Zhenghao Liu, Xiaoyuan Yi, Liner Yang, Shuo Wang, Yu Gu, Ge Yu, Xing Xie, Shuang-Hua Yang

It proposes a dual-view legal clue reasoning mechanism, which derives from two reasoning chains of judges: 1) Law Case Reasoning, which makes legal judgments according to the judgment experiences learned from analogy/confusing legal cases; 2) Legal Ground Reasoning, which lies in matching the legal clues between criminal cases and legal decisions.

CDEval: A Benchmark for Measuring the Cultural Dimensions of Large Language Models

1 code implementation28 Nov 2023 Yuhang Wang, Yanxu Zhu, Chao Kong, Shuyu Wei, Xiaoyuan Yi, Xing Xie, Jitao Sang

This benchmark serves as a valuable resource for cultural studies in LLMs, paving the way for more culturally aware and sensitive models.

Knowledge Plugins: Enhancing Large Language Models for Domain-Specific Recommendations

no code implementations16 Nov 2023 Jing Yao, Wei Xu, Jianxun Lian, Xiting Wang, Xiaoyuan Yi, Xing Xie

In this paper, we propose a general paradigm that augments LLMs with DOmain-specific KnowledgE to enhance their performance on practical applications, namely DOKE.

Collaborative Filtering Recommendation Systems +1

Value FULCRA: Mapping Large Language Models to the Multidimensional Spectrum of Basic Human Values

no code implementations15 Nov 2023 Jing Yao, Xiaoyuan Yi, Xiting Wang, Yifan Gong, Xing Xie

The rapid advancement of Large Language Models (LLMs) has attracted much attention to value alignment for their responsible development.

Fairness

Unpacking the Ethical Value Alignment in Big Models

no code implementations26 Oct 2023 Xiaoyuan Yi, Jing Yao, Xiting Wang, Xing Xie

Big models have greatly advanced AI's ability to understand, generate, and manipulate information and content, enabling numerous applications.

Ethics

From Instructions to Intrinsic Human Values -- A Survey of Alignment Goals for Big Models

no code implementations23 Aug 2023 Jing Yao, Xiaoyuan Yi, Xiting Wang, Jindong Wang, Xing Xie

Big models, exemplified by Large Language Models (LLMs), are models typically pre-trained on massive data and comprised of enormous parameters, which not only obtain significantly improved performance across diverse tasks but also present emergent capabilities absent in smaller models.

A Survey on Evaluation of Large Language Models

1 code implementation6 Jul 2023 Yupeng Chang, Xu Wang, Jindong Wang, Yuan Wu, Linyi Yang, Kaijie Zhu, Hao Chen, Xiaoyuan Yi, Cunxiang Wang, Yidong Wang, Wei Ye, Yue Zhang, Yi Chang, Philip S. Yu, Qiang Yang, Xing Xie

Large language models (LLMs) are gaining increasing popularity in both academia and industry, owing to their unprecedented performance in various applications.

Ethics

KEST: Kernel Distance Based Efficient Self-Training for Improving Controllable Text Generation

1 code implementation17 Jun 2023 Yuxi Feng, Xiaoyuan Yi, Laks V. S. Lakshmanan, Xing Xie

Self-training (ST) has come to fruition in language understanding tasks by producing pseudo labels, which reduces the labeling bottleneck of language model fine-tuning.

Diversity Language Modelling +1

Efficient Cross-Lingual Transfer for Chinese Stable Diffusion with Images as Pivots

no code implementations19 May 2023 Jinyi Hu, Xu Han, Xiaoyuan Yi, Yutong Chen, Wenhao Li, Zhiyuan Liu, Maosong Sun

IAP optimizes only a separate Chinese text encoder with all other parameters fixed to align Chinese semantics space to the English one in CLIP.

Cross-Lingual Transfer Image Generation

DuNST: Dual Noisy Self Training for Semi-Supervised Controllable Text Generation

1 code implementation16 Dec 2022 Yuxi Feng, Xiaoyuan Yi, Xiting Wang, Laks V. S. Lakshmanan, Xing Xie

Augmented by only self-generated pseudo text, generation models over-emphasize exploitation of the previously learned space, suffering from a constrained generalization boundary.

Attribute Diversity +1

Evade the Trap of Mediocrity: Promoting Diversity and Novelty in Text Generation via Concentrating Attention

1 code implementation14 Nov 2022 Wenhao Li, Xiaoyuan Yi, Jinyi Hu, Maosong Sun, Xing Xie

In this work, we dig into the intrinsic mechanism of this problem and found that sparser attention values in Transformer could improve diversity.

Attribute Diversity +1

Recurrence Boosts Diversity! Revisiting Recurrent Latent Variable in Transformer-Based Variational AutoEncoder for Diverse Text Generation

no code implementations22 Oct 2022 Jinyi Hu, Xiaoyuan Yi, Wenhao Li, Maosong Sun, Xing Xie

We demonstrate that TRACE could enhance the entanglement of each segment and preceding latent variables and deduce a non-zero lower bound of the KL term, providing a theoretical guarantee of generation diversity.

Diversity Text Generation

Self-explaining deep models with logic rule reasoning

1 code implementation13 Oct 2022 Seungeon Lee, Xiting Wang, Sungwon Han, Xiaoyuan Yi, Xing Xie, Meeyoung Cha

We present SELOR, a framework for integrating self-explaining capabilities into a given deep model to achieve both high prediction performance and human precision.

CCPM: A Chinese Classical Poetry Matching Dataset

1 code implementation3 Jun 2021 Wenhao Li, Fanchao Qi, Maosong Sun, Xiaoyuan Yi, Jiarui Zhang

We hope this dataset can further enhance the study on incorporating deep semantics into the understanding and generation system of Chinese classical poetry.

Translation

MixPoet: Diverse Poetry Generation via Learning Controllable Mixed Latent Space

no code implementations13 Mar 2020 Xiaoyuan Yi, Ruoyu Li, Cheng Yang, Wenhao Li, Maosong Sun

Though recent neural models make prominent progress in some criteria of poetry quality, generated poems still suffer from the problem of poor diversity.

Diversity

Jiuge: A Human-Machine Collaborative Chinese Classical Poetry Generation System

no code implementations ACL 2019 Guo Zhipeng, Xiaoyuan Yi, Maosong Sun, Wenhao Li, Cheng Yang, Jiannan Liang, Huimin Chen, Yuhui Zhang, Ruoyu Li

By exposing the options of poetry genres, styles and revision modes, Jiuge, acting as a professional assistant, allows constant and active participation of users in poetic creation.

Cultural Vocal Bursts Intensity Prediction

Stylistic Chinese Poetry Generation via Unsupervised Style Disentanglement

no code implementations EMNLP 2018 Cheng Yang, Maosong Sun, Xiaoyuan Yi, Wenhao Li

The ability to write diverse poems in different styles under the same poetic imagery is an important characteristic of human poetry writing.

Disentanglement Machine Translation +1

Chinese Poetry Generation with a Working Memory Model

1 code implementation12 Sep 2018 Xiaoyuan Yi, Maosong Sun, Ruoyu Li, Zonghan Yang

Different from previous methods, our model explicitly maintains topics and informative limited history in a neural memory.

Cultural Vocal Bursts Intensity Prediction

Chinese Poetry Generation with a Salient-Clue Mechanism

no code implementations CONLL 2018 Xiaoyuan Yi, Ruoyu Li, Maosong Sun

As a precious part of the human cultural heritage, Chinese poetry has influenced people for generations.

Generating Chinese Classical Poems with RNN Encoder-Decoder

no code implementations6 Apr 2016 Xiaoyuan Yi, Ruoyu Li, Maosong Sun

We take the generation of Chinese classical poem lines as a sequence-to-sequence learning problem, and build a novel system based on the RNN Encoder-Decoder structure to generate quatrains (Jueju in Chinese), with a topic word as input.

Decoder

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