Search Results for author: Tianlin Zhang

Found 13 papers, 8 papers with code

MetaAligner: Towards Generalizable Multi-Objective Alignment of Language Models

1 code implementation25 Mar 2024 Kailai Yang, Zhiwei Liu, Qianqian Xie, Jimin Huang, Tianlin Zhang, Sophia Ananiadou

Recent advancements in large language models (LLMs) aim to tackle heterogeneous human expectations and values via multi-objective preference alignment.

In-Context Learning

EmoLLMs: A Series of Emotional Large Language Models and Annotation Tools for Comprehensive Affective Analysis

1 code implementation16 Jan 2024 Zhiwei Liu, Kailai Yang, Tianlin Zhang, Qianqian Xie, Zeping Yu, Sophia Ananiadou

In this paper, we propose EmoLLMs, the first series of open-sourced instruction-following LLMs for comprehensive affective analysis based on fine-tuning various LLMs with instruction data, the first multi-task affective analysis instruction dataset (AAID) with 234K data samples based on various classification and regression tasks to support LLM instruction tuning, and a comprehensive affective evaluation benchmark (AEB) with 14 tasks from various sources and domains to test the generalization ability of LLMs.

Instruction Following regression +1

Rethinking Large Language Models in Mental Health Applications

no code implementations19 Nov 2023 Shaoxiong Ji, Tianlin Zhang, Kailai Yang, Sophia Ananiadou, Erik Cambria

Large Language Models (LLMs) have become valuable assets in mental health, showing promise in both classification tasks and counseling applications.

Emotion Detection for Misinformation: A Review

no code implementations1 Nov 2023 Zhiwei Liu, Tianlin Zhang, Kailai Yang, Paul Thompson, Zeping Yu, Sophia Ananiadou

The emotions and sentiments of netizens, as expressed in social media posts and news, constitute important factors that can help to distinguish fake news from genuine news and to understand the spread of rumors.

Fake News Detection Misinformation

A Bipartite Graph is All We Need for Enhancing Emotional Reasoning with Commonsense Knowledge

1 code implementation9 Aug 2023 Kailai Yang, Tianlin Zhang, Shaoxiong Ji, Sophia Ananiadou

However, most previous knowledge infusion methods perform empirical knowledge filtering and design highly customized architectures for knowledge interaction with the utterances, which can discard useful knowledge aspects and limit their generalizability to different knowledge sources.

Opinion Mining

Disentangled Variational Autoencoder for Emotion Recognition in Conversations

1 code implementation23 May 2023 Kailai Yang, Tianlin Zhang, Sophia Ananiadou

We also enhance the disentangled representations by introducing VAD supervision signals from a sentiment lexicon and minimising the mutual information between VAD distributions.

Emotion Recognition Response Generation

Domain-specific Continued Pretraining of Language Models for Capturing Long Context in Mental Health

no code implementations20 Apr 2023 Shaoxiong Ji, Tianlin Zhang, Kailai Yang, Sophia Ananiadou, Erik Cambria, Jörg Tiedemann

In the mental health domain, domain-specific language models are pretrained and released, which facilitates the early detection of mental health conditions.

Emotion fusion for mental illness detection from social media: A survey

no code implementations19 Apr 2023 Tianlin Zhang, Kailai Yang, Shaoxiong Ji, Sophia Ananiadou

In this article, we provide a comprehensive survey of approaches to mental illness detection in social media that incorporate emotion fusion.

Cluster-Level Contrastive Learning for Emotion Recognition in Conversations

1 code implementation7 Feb 2023 Kailai Yang, Tianlin Zhang, Hassan Alhuzali, Sophia Ananiadou

To address these issues, we propose a novel low-dimensional Supervised Cluster-level Contrastive Learning (SCCL) method, which first reduces the high-dimensional SCL space to a three-dimensional affect representation space Valence-Arousal-Dominance (VAD), then performs cluster-level contrastive learning to incorporate measurable emotion prototypes.

Contrastive Learning Emotion Recognition

MentalBERT: Publicly Available Pretrained Language Models for Mental Healthcare

no code implementations LREC 2022 Shaoxiong Ji, Tianlin Zhang, Luna Ansari, Jie Fu, Prayag Tiwari, Erik Cambria

Mental health is a critical issue in modern society, and mental disorders could sometimes turn to suicidal ideation without adequate treatment.

Cannot find the paper you are looking for? You can Submit a new open access paper.