21 citations · 55 across the 20 of their papers we have counts for
21 papers
Belief Memory: Agent Memory Under Partial Observability
Junfeng Liao, Qizhou Wang, Jianing Zhu +3
LLM agents that operate over long context depend on external memory to accumulate knowledge over time. However, existing methods typically store each observation as a single determ…
When Personalization Tricks Detectors: The Feature-Inversion Trap in Machine-Generated Text Detection
Lang Gao, Xuhui Li, Chenxi Wang +7
Large language models (LLMs) have grown more powerful in language generation, producing fluent text and even imitating personal style. Yet, this ability also heightens the risk of…
Unify Graph Learning with Text: Unleashing LLM Potentials for Session Search
Songhao Wu, Quan Tu, Hong Liu +6
Session search involves a series of interactive queries and actions to fulfill user's complex information need. Current strategies typically prioritize sequential modeling for deep…
The Truth Becomes Clearer Through Debate! Multi-Agent Systems with Large Language Models Unmask Fake News
Yuhan Liu, Yuxuan Liu, Xiaoqing Zhang +2
In today's digital environment, the rapid propagation of fake news via social networks poses significant social challenges. Most existing detection methods either employ traditiona…
Pastiche Novel Generation Creating: Fan Fiction You Love in Your Favorite Author's Style
Xueran Han, Yuhan Liu, Mingzhe Li +5
Great novels create immersive worlds with rich character arcs, well-structured plots, and nuanced writing styles. However, current novel generation methods often rely on brief, sim…
Thinking Before Running! Efficient Code Generation with Thorough Exploration and Optimal Refinement
Xiaoqing Zhang, Yuhan Liu, Flood Sung +3
Code generation is crucial in software engineering for automating the coding process efficiently. While test-time computation methods show promise, they suffer from high latency du…
More is not always better? Enhancing Many-Shot In-Context Learning with Differentiated and Reweighting Objectives
Xiaoqing Zhang, Ang Lv, Yuhan Liu +6
Large language models (LLMs) excel at few-shot in-context learning (ICL) without requiring parameter updates. However, as ICL demonstrations increase from a few to many, performanc…
A Large-scale Time-aware Agents Simulation for Influencer Selection in Digital Advertising Campaigns
Xiaoqing Zhang, Xiuying Chen, Yuhan Liu +3
In the digital world, influencers are pivotal as opinion leaders, shaping the views and choices of their influencees. Modern advertising often follows this trend, where marketers c…
The Stepwise Deception: Simulating the Evolution from True News to Fake News with LLM Agents
Yuhan Liu, Zirui Song, Juntian Zhang +3
With the growing spread of misinformation online, understanding how true news evolves into fake news has become crucial for early detection and prevention. However, previous resear…
Flexible and Adaptable Summarization via Expertise Separation
Xiuying Chen, Mingzhe Li, Shen Gao +5
A proficient summarization model should exhibit both flexibility -- the capacity to handle a range of in-domain summarization tasks, and adaptability -- the competence to acquire n…
Leveraging 2D Information for Long-term Time Series Forecasting with Vanilla Transformers
Xin Cheng, Xiuying Chen, Shuqi Li +4
Time series prediction is crucial for understanding and forecasting complex dynamics in various domains, ranging from finance and economics to climate and healthcare. Based on Tran…
Selecting Query-bag as Pseudo Relevance Feedback for Information-seeking Conversations
Xiaoqing Zhang, Xiuying Chen, Shen Gao +4
Information-seeking dialogue systems are widely used in e-commerce systems, with answers that must be tailored to fit the specific settings of the online system. Given the user que…
SAGraph: A Large-Scale Social Graph Dataset with Comprehensive Context for Influencer Selection in Marketing
Xiaoqing Zhang, Yuhan Liu, Jianzhou Wang +3
Influencer marketing campaign success heavily depends on identifying key opinion leaders who can effectively leverage their credibility and reach to promote products or services. T…
From Skepticism to Acceptance: Simulating the Attitude Dynamics Toward Fake News
Yuhan Liu, Xiuying Chen, Xiaoqing Zhang +3
In the digital era, the rapid propagation of fake news and rumors via social networks brings notable societal challenges and impacts public opinion regulation. Traditional fake new…
Decouple knowledge from parameters for plug-and-play language modeling
Xin Cheng, Yankai Lin, Xiuying Chen +2
Pre-trained language models(PLM) have made impressive results in various NLP tasks. It has been revealed that one of the key factors to their success is the parameters of these mod…
Lift Yourself Up: Retrieval-augmented Text Generation with Self Memory
Xin Cheng, Di Luo, Xiuying Chen +3
With direct access to human-written reference as memory, retrieval-augmented generation has achieved much progress in a wide range of text generation tasks. Since better memory wou…
EZInterviewer: To Improve Job Interview Performance with Mock Interview Generator
Mingzhe Li, Xiuying Chen, Weiheng Liao +4
Interview has been regarded as one of the most crucial step for recruitment. To fully prepare for the interview with the recruiters, job seekers usually practice with mock intervie…
How does Truth Evolve into Fake News? An Empirical Study of Fake News Evolution
Mingfei Guo, Xiuying Chen, Juntao Li +2
Automatically identifying fake news from the Internet is a challenging problem in deception detection tasks. Online news is modified constantly during its propagation, e.g., malici…
The Style-Content Duality of Attractiveness: Learning to Write Eye-Catching Headlines via Disentanglement
Mingzhe Li, Xiuying Chen, Min Yang +3
Eye-catching headlines function as the first device to trigger more clicks, bringing reciprocal effect between producers and viewers. Producers can obtain more traffic and profits,…
Reasoning in Dialog: Improving Response Generation by Context Reading Comprehension
Xiuying Chen, Zhi Cui, Jiayi Zhang +5
In multi-turn dialog, utterances do not always take the full form of sentences \cite{Carbonell1983DiscoursePA}, which naturally makes understanding the dialog context more difficul…
From Standard Summarization to New Tasks and Beyond: Summarization with Manifold Information
Shen Gao, Xiuying Chen, Zhaochun Ren +2
Text summarization is the research area aiming at creating a short and condensed version of the original document, which conveys the main idea of the document in a few words. This…