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The advancement of large language model (LLM) based artificial intelligence technologies has been a game-changer, particularly in sentiment analysis. This progress has enabled a shift from highly specialized research environments to…

Software Engineering · Computer Science 2024-10-24 Chaofeng Zhang , Jia Hou , Xueting Tan , Gaolei Li , Caijuan Chen

Accurately retrieving relevant bid keywords for user queries is critical in Sponsored Search but remains challenging, particularly for short, ambiguous queries. Existing dense and generative retrieval models often fail to capture nuanced…

Information Retrieval · Computer Science 2024-10-21 Akash Kumar Mohankumar , Gururaj K , Gagan Madan , Amit Singh

Recent immense breakthroughs in generative models such as in GPT4 have precipitated re-imagined ubiquitous usage of these models in all applications. One area that can benefit by improvements in artificial intelligence (AI) is healthcare.…

Computation and Language · Computer Science 2023-06-06 Wen-wai Yim , Yujuan Fu , Asma Ben Abacha , Neal Snider , Thomas Lin , Meliha Yetisgen

This paper proposes a comprehensive framework for the generation of covert advertisements within Conversational AI systems, along with robust techniques for their detection. It explores how subtle promotional content can be crafted within…

Computation and Language · Computer Science 2025-09-19 Arka Dutta , Agrik Majumdar , Sombrata Biswas , Dipankar Das , Sivaji Bandyopadhyay

Retriever-augmented generation (RAG) has become a widely adopted approach for enhancing the factual accuracy of large language models (LLMs). While current benchmarks evaluate the performance of RAG methods from various perspectives, they…

Information Retrieval · Computer Science 2025-04-08 Kepu Zhang , Zhongxiang Sun , Weijie Yu , Xiaoxue Zang , Kai Zheng , Yang Song , Han Li , Jun Xu

Social media enables dynamic user engagement with trending topics, and recent research has explored the potential of large language models (LLMs) for response generation. While some studies investigate LLMs as agents for simulating user…

Computation and Language · Computer Science 2025-02-18 Zhongyi Qiu , Hanjia Lyu , Wei Xiong , Jiebo Luo

The widespread adoption of reinforcement learning-based alignment highlights the growing importance of reward models. Various benchmarks have been built to evaluate reward models in various domains and scenarios. However, a significant gap…

Computation and Language · Computer Science 2026-03-16 Hui Huang , Yancheng He , Wei Liu , Muyun Yang , Jiaheng Liu , Kehai Chen , Bing Xu , Conghui Zhu , Hailong Cao , Tiejun Zhao

Reward models are critical in techniques like Reinforcement Learning from Human Feedback (RLHF) and Inference Scaling Laws, where they guide language model alignment and select optimal responses. Despite their importance, existing reward…

Computation and Language · Computer Science 2024-10-22 Yantao Liu , Zijun Yao , Rui Min , Yixin Cao , Lei Hou , Juanzi Li

Large Language Models (LLMs) based autonomous agents demonstrate multifaceted capabilities to contribute substantially to economic production. However, existing benchmarks remain focused on single agentic capability, failing to capture…

Artificial Intelligence · Computer Science 2026-04-24 Keyu Li , Junhao Shi , Yang Xiao , Mohan Jiang , Jie Sun , Yunze Wu , Dayuan Fu , Shijie Xia , Xiaojie Cai , Tianze Xu , Weiye Si , Wenjie Li , Dequan Wang , Pengfei Liu

This paper contains what the Georgetown InfoSense group has done in regard to solving the challenges presented by TREC iKAT 2023. Our submitted runs outperform the median runs by a significant margin, exhibiting superior performance in nDCG…

Computation and Language · Computer Science 2023-11-17 Quinn Patwardhan , Grace Hui Yang

We introduce EQ-Bench, a novel benchmark designed to evaluate aspects of emotional intelligence in Large Language Models (LLMs). We assess the ability of LLMs to understand complex emotions and social interactions by asking them to predict…

Computation and Language · Computer Science 2024-01-04 Samuel J. Paech

Personalized content marketing has become a crucial strategy for digital platforms, aiming to deliver tailored advertisements and recommendations that match user preferences. Traditional recommendation systems often suffer from two…

Information Retrieval · Computer Science 2025-09-23 Ruihan Luo , Xuanjing Chen , Ziyang Ding

The Expectation-Maximization (EM) algorithm is one of the most popular methods used to solve the problem of parametric distribution-based clustering in unsupervised learning. In this paper, we propose to analyze a generalized EM (GEM)…

Optimization and Control · Mathematics 2021-05-19 Sarthak Chatterjee , Orlando Romero , Sérgio Pequito

This study compares the performance of AI-generated and human-written product descriptions using a multifaceted evaluation model. We analyze descriptions for 100 products generated by four AI models (Gemma 2B, LLAMA, GPT2, and ChatGPT 4)…

Computation and Language · Computer Science 2024-12-30 Sanjukta Ghosh

The Graphical User Interface (GUI) is pivotal for human interaction with the digital world, enabling efficient device control and the completion of complex tasks. Recent progress in Large Language Models (LLMs) and Vision Language Models…

Artificial Intelligence · Computer Science 2024-06-14 Danyang Zhang , Zhennan Shen , Rui Xie , Situo Zhang , Tianbao Xie , Zihan Zhao , Siyuan Chen , Lu Chen , Hongshen Xu , Ruisheng Cao , Kai Yu

Autonomous agents powered by large language models (LLMs) promise to accelerate scientific discovery end-to-end, but rigorously evaluating their capacity for verifiable discovery remains a central challenge. Existing benchmarks face a…

Artificial Intelligence · Computer Science 2026-02-04 Zhen Wang , Fan Bai , Zhongyan Luo , Jinyan Su , Kaiser Sun , Xinle Yu , Jieyuan Liu , Kun Zhou , Claire Cardie , Mark Dredze , Eric P. Xing , Zhiting Hu

The emergence of pretrained large language models has led to the deployment of a range of social chatbots for chitchat. Although these chatbots demonstrate language ability and fluency, they are not guaranteed to be engaging and can…

Dialogue response generation requires an agent to generate a response according to the current dialogue history, in terms of which two-party dialogues have been well studied, but leaving a great gap for multi-party dialogues at the same…

Computation and Language · Computer Science 2023-05-23 Yiyang Li , Hai Zhao

Large language models are increasingly applied to various development scenarios. However, in on-chain transaction scenarios, even a minor error can cause irreversible loss for users. Existing evaluations often overlook execution accuracy…

Computation and Language · Computer Science 2026-04-08 Pei Yang , Wanyi Chen , Ke Wang , Lynn Ai , Eric Yang , Tianyu Shi

A Comparison of Independent and Joint Fine-tuning Strategies for Retrieval-Augmented Generation Download PDF Neal Gregory Lawton, Alfy Samuel, Anoop Kumar, Daben Liu Published: 20 Aug 2025, Retrieval augmented generation (RAG) is a popular…

Computation and Language · Computer Science 2025-10-21 Neal Gregory Lawton , Alfy Samuel , Anoop Kumar , Daben Liu