Search Results for author: Xiaoyuan Yi

Found 43 papers, 20 papers with code

Unintended Harms of Value-Aligned LLMs: Psychological and Empirical Insights

1 code implementation6 Jun 2025 Sooyung Choi, JaeHyeok Lee, Xiaoyuan Yi, Jing Yao, Xing Xie, JinYeong Bak

Using a dataset with detailed safety categories, we find significant correlations between value alignment and safety risks, supported by psychological hypotheses.

AdAEM: An Adaptively and Automated Extensible Measurement of LLMs' Value Difference

no code implementations18 May 2025 Shitong Duan, Xiaoyuan Yi, Peng Zhang, Dongkuan Xu, Jing Yao, Tun Lu, Ning Gu, Xing Xie

Assessing Large Language Models (LLMs)' underlying value differences enables comprehensive comparison of their misalignment, cultural adaptability, and biases.

Informativeness

Leveraging Implicit Sentiments: Enhancing Reliability and Validity in Psychological Trait Evaluation of LLMs

1 code implementation26 Mar 2025 Huanhuan Ma, Haisong Gong, Xiaoyuan Yi, Xing Xie, Dongkuan Xu

Through extensive experiments, we demonstrate that: 1) CSI effectively captures nuanced emotional patterns, revealing significant variation in LLMs across languages and contexts; 2) Compared to current approaches, CSI significantly improves reliability, yielding more consistent results; and 3) The correlation between CSI scores and the sentiment of LLM's real-world outputs exceeds 0. 85, demonstrating its strong validity in predicting LLM behavior.

Research on Superalignment Should Advance Now with Parallel Optimization of Competence and Conformity

no code implementations8 Mar 2025 HyunJin Kim, Xiaoyuan Yi, Jing Yao, Muhua Huang, JinYeong Bak, James Evans, Xing Xie

The recent leap in AI capabilities, driven by big generative models, has sparked the possibility of achieving Artificial General Intelligence (AGI) and further triggered discussions on Artificial Superintelligence (ASI), a system surpassing all humans across all domains.

Benchmarking Retrieval-Augmented Generation in Multi-Modal Contexts

2 code implementations24 Feb 2025 Zhenghao Liu, Xingsheng Zhu, Tianshuo Zhou, Xinyi Zhang, Xiaoyuan Yi, Yukun Yan, Yu Gu, Ge Yu, Maosong Sun

This paper introduces Multi-Modal Retrieval-Augmented Generation (M^2RAG), a benchmark designed to evaluate the effectiveness of Multi-modal Large Language Models (MLLMs) in leveraging knowledge from multi-modal retrieval documents.

Benchmarking Fact Verification +6

PIP-KAG: Mitigating Knowledge Conflicts in Knowledge-Augmented Generation via Parametric Pruning

1 code implementation21 Feb 2025 Pengcheng Huang, Zhenghao Liu, Yukun Yan, Xiaoyuan Yi, Hao Chen, Zhiyuan Liu, Maosong Sun, Tong Xiao, Ge Yu, Chenyan Xiong

Knowledge-Augmented Generation (KAG) has shown great promise in updating the internal memory of Large Language Models (LLMs) by integrating external knowledge.

Hallucination

Value Compass Leaderboard: A Platform for Fundamental and Validated Evaluation of LLMs Values

no code implementations13 Jan 2025 Jing Yao, Xiaoyuan Yi, Shitong Duan, Jindong Wang, Yuzhuo Bai, Muhua Huang, Peng Zhang, Tun Lu, Zhicheng Dou, Maosong Sun, Xing Xie

As Large Language Models (LLMs) achieve remarkable breakthroughs, aligning their values with humans has become imperative for their responsible development and customized applications.

The Road to Artificial SuperIntelligence: A Comprehensive Survey of Superalignment

no code implementations21 Dec 2024 HyunJin Kim, Xiaoyuan Yi, Jing Yao, Jianxun Lian, Muhua Huang, Shitong Duan, JinYeong Bak, Xing Xie

The emergence of large language models (LLMs) has sparked the possibility of about Artificial Superintelligence (ASI), a hypothetical AI system surpassing human intelligence.

Survey

Embedding an Ethical Mind: Aligning Text-to-Image Synthesis via Lightweight Value Optimization

1 code implementation16 Oct 2024 Xingqi Wang, Xiaoyuan Yi, Xing Xie, Jia Jia

To optimize the value encoder, we also develop a framework to automatically construct a text-image preference dataset of 86k (prompt, aligned image, violating image, value principle) samples.

Image Generation

Elephant in the Room: Unveiling the Impact of Reward Model Quality in Alignment

no code implementations26 Sep 2024 Yan Liu, Xiaoyuan Yi, Xiaokang Chen, Jing Yao, Jingwei Yi, Daoguang Zan, Zheng Liu, Xing Xie, Tsung-Yi Ho

Despite the vital role reward models play in alignment, previous works have consistently overlooked their performance and used off-the-shelf reward models arbitrarily without verification, rendering the reward model ``\emph{an elephant in the room}''.

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, Ziang Xiao, Shu Wang, Xing Xie

Unlike traditional adaptive testing methods that rely on a static test item pool, GETA probes the underlying moral boundaries of LLMs by dynamically generating test items tailored to model capability.

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 with Human Negative Samples via Distributional Dispreference Optimization

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

Large language models (LLMs) have revolutionized the role of AI, yet pose potential social risks.

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 Fine-grained Representations for Legal Judgment Prediction via a Dual-View Contrastive Learning

1 code implementation27 Jan 2024 Buqiang Xu, Xin Dai, Zhenghao Liu, Huiyuan Xie, Xiaoyuan Yi, Shuo Wang, Yukun Yan, Liner Yang, Yu Gu, Ge Yu

In this paper, we propose LegalDuet, which continuously pretrains language models to learn a more tailored embedding space for representing legal cases.

Contrastive Learning

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

1 code implementation16 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 Survey

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 Modeling +2

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.

Deep Learning

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 model

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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