2 citations · 3 across the 12 of their papers we have counts for
13 papers
When Models Edit Too Much: On the Fidelity of Minimal Code Edits
Tongyao Zhu, Wei Hern Lim, Min-Yen Kan
Large language models (LLMs) are increasingly used to edit existing code, but correctness alone is not enough: useful repairs should also be minimal, reviewable, and faithful to th…
KAHAN: Knowledge-Augmented Hierarchical Analysis and Narration for Financial Data Narration
Yajing Yang, Tony Deng, Min-Yen Kan
We propose KAHAN, a knowledge-augmented hierarchical framework that systematically extracts insights from raw tabular data at entity, pairwise, group, and system levels. KAHAN uniq…
Improving Conversational Recommendation with Contextual Adaptation of External Recommenders and LLM-based Reranking
Chuang Li, Weida Liang, Hengchang Hu +4
We tackle the challenge of integrating large language models (LLMs) with external recommender systems to enhance domain expertise in conversational recommendation (CRS). Current LL…
Seeing Through Deception: Uncovering Misleading Creator Intent in Multimodal News with Vision-Language Models
Jiaying Wu, Fanxiao Li, Zihang Fu +2
The impact of multimodal misinformation arises not only from factual inaccuracies but also from the misleading narratives that creators deliberately embed. Interpreting such creato…
SkyLadder: Better and Faster Pretraining via Context Window Scheduling
Tongyao Zhu, Qian Liu, Haonan Wang +4
Recent advancements in LLM pretraining have featured ever-expanding context windows to process longer sequences. However, our pilot study reveals that models pretrained with shorte…
Evaluating Sakana's AI Scientist: Bold Claims, Mixed Results, and a Promising Future?
Joeran Beel, Min-Yen Kan, Moritz Baumgart
A major step toward Artificial General Intelligence (AGI) and Super Intelligence is AI's ability to autonomously conduct research - what we term Artificial Research Intelligence (A…
DataTales: A Benchmark for Real-World Intelligent Data Narration
Yajing Yang, Qian Liu, Min-Yen Kan
We introduce DataTales, a novel benchmark designed to assess the proficiency of language models in data narration, a task crucial for transforming complex tabular data into accessi…
CCSBench: Evaluating Compositional Controllability in LLMs for Scientific Document Summarization
Yixi Ding, Jiaying Wu, Tongyao Zhu +3
To broaden the dissemination of scientific knowledge to diverse audiences, it is desirable for scientific document summarization systems to simultaneously control multiple attribut…
Incorporating External Knowledge and Goal Guidance for LLM-based Conversational Recommender Systems
Chuang Li, Yang Deng, Hengchang Hu +2
This paper aims to efficiently enable large language models (LLMs) to use external knowledge and goal guidance in conversational recommender system (CRS) tasks. Advanced LLMs (e.g.…
ISQA: Informative Factuality Feedback for Scientific Summarization
Zekai Li, Yanxia Qin, Qian Liu +1
We propose Iterative Facuality Refining on Informative Scientific Question-Answering (ISQA) feedback\footnote{Code is available at \url{https://github.com/lizekai-richard/isqa}}, a…
Discrete Semantic Tokenization for Deep CTR Prediction
Qijiong Liu, Hengchang Hu, Jiahao Wu +3
Incorporating item content information into click-through rate (CTR) prediction models remains a challenge, especially with the time and space constraints of industrial scenarios.…
Beyond Memorization: The Challenge of Random Memory Access in Language Models
Tongyao Zhu, Qian Liu, Liang Pang +3
Recent developments in Language Models (LMs) have shown their effectiveness in NLP tasks, particularly in knowledge-intensive tasks. However, the mechanisms underlying knowledge st…
Lightweight Modality Adaptation to Sequential Recommendation via Correlation Supervision
Hengchang Hu, Qijiong Liu, Chuang Li +1
In Sequential Recommenders (SR), encoding and utilizing modalities in an end-to-end manner is costly in terms of modality encoder sizes. Two-stage approaches can mitigate such conc…