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Signal Temporal Logic (STL) is expressive formal language that specifies spatio-temporal requirements in robotics. Its quantitative robustness semantics can be easily integrated with optimization-based control frameworks. However, STL…

Robotics · Computer Science 2026-03-10 Tianhao Wu , Yiwei Lyu

Retrieval-Augmented Language Models (RALMs) face significant challenges in reducing factual errors, particularly in document relevance evaluation and knowledge integration. We introduce a framework for structured relevance assessment that…

Artificial Intelligence · Computer Science 2025-07-30 Aryan Raj , Astitva Veer Garg , Anitha D

We explore a novel approach for Semantic Role Labeling (SRL) by casting it as a sequence-to-sequence process. We employ an attention-based model enriched with a copying mechanism to ensure faithful regeneration of the input sequence, while…

Computation and Language · Computer Science 2018-07-10 Angel Daza , Anette Frank

Semi-supervised regression (SSR), which aims to predict continuous scores for samples while reducing the reliance on large-scale labeled data, has recently attracted considerable attention across various applications, including computer…

Machine Learning · Computer Science 2026-05-28 Ye Su , Hezhe Qiao , Wei Huang , Lin Chen

Preference-based Reinforcement Learning (PbRL) entails a variety of approaches for aligning models with human intent to alleviate the burden of reward engineering. However, most previous PbRL work has not investigated the robustness to…

Machine Learning · Computer Science 2025-06-17 Sara Rajaram , R. James Cotton , Fabian H. Sinz

The Stable Roommates problem (SR) is characterized by the preferences of agents over other agents as roommates: each agent ranks all others in strict order of preference. A solution to SR is then a partition of the agents into pairs so that…

Artificial Intelligence · Computer Science 2020-08-10 Esra Erdem , Muge Fidan , David Manlove , Patrick Prosser

The goal of a recommendation system is to model the relevance between each user and each item through the user-item interaction history, so that maximize the positive samples score and minimize negative samples. Currently, two popular loss…

Information Retrieval · Computer Science 2022-07-08 Chun Yang , Shicai Fan

Recent advancements in large language models (LLMs) have shown remarkable progress, yet their ability to solve complex problems remains limited. In this work, we introduce Cumulative Reasoning (CR), a structured framework that enhances LLM…

Artificial Intelligence · Computer Science 2026-05-22 Yifan Zhang , Jingqin Yang , Yang Yuan , Andrew Chi-Chih Yao

Large language models (LLMs) equipped with retrieval--the Retrieval-Augmented Generation (RAG) paradigm--should combine their parametric knowledge with external evidence, yet in practice they often hallucinate, over-trust noisy snippets, or…

Artificial Intelligence · Computer Science 2026-01-13 Hua Ye , Siyuan Chen , Ziqi Zhong , Canran Xiao , Haoliang Zhang , Yuhan Wu , Fei Shen

This paper explores the use of Answer Set Programming (ASP) in solving Distributed Constraint Optimization Problems (DCOPs). The paper provides the following novel contributions: (1) It shows how one can formulate DCOPs as logic programs;…

Multiagent Systems · Computer Science 2017-05-12 Tiep Le , Tran Cao Son , Enrico Pontelli , William Yeoh

Spoken language understanding (SLU) is an essential task for machines to understand human speech for better interactions. However, errors from the automatic speech recognizer (ASR) usually hurt the understanding performance. In reality, ASR…

Computation and Language · Computer Science 2022-06-28 Ya-Hsin Chang , Yun-Nung Chen

Retrieval-augmented language models (RALMs) have recently shown great potential in mitigating the limitations of implicit knowledge in LLMs, such as untimely updating of the latest expertise and unreliable retention of long-tail knowledge.…

Computation and Language · Computer Science 2024-10-07 Zile Qiao , Wei Ye , Yong Jiang , Tong Mo , Pengjun Xie , Weiping Li , Fei Huang , Shikun Zhang

The constraint satisfaction problem (CSP) is a general problem central to computer science and artificial intelligence. Although the CSP is NP-hard in general, considerable effort has been spent on identifying tractable subclasses. The main…

Artificial Intelligence · Computer Science 2014-07-09 David A. Cohen , Martin C. Cooper , Páidí Creed , András Z. Salamon

In recent years, Multi-View Clustering (MVC) has attracted increasing attention for its potential to reduce the annotation burden associated with large datasets. The aim of MVC is to exploit the inherent consistency and complementarity…

Machine Learning · Computer Science 2024-07-12 Zhangci Xiong , Meng Cao

With the development of the online education system, personalized education recommendation has played an essential role. In this paper, we focus on developing path recommendation systems that aim to generating and recommending an entire…

Information Retrieval · Computer Science 2023-06-08 Xianyu Chen , Jian Shen , Wei Xia , Jiarui Jin , Yakun Song , Weinan Zhang , Weiwen Liu , Menghui Zhu , Ruiming Tang , Kai Dong , Dingyin Xia , Yong Yu

Domain adaptation is an important but challenging task. Most of the existing domain adaptation methods struggle to extract the domain-invariant representation on the feature space with entangling domain information and semantic information.…

Computer Vision and Pattern Recognition · Computer Science 2020-12-23 Ruichu Cai , Zijian Li , Pengfei Wei , Jie Qiao , Kun Zhang , Zhifeng Hao

Consistent query answering is an inconsistency tolerant approach to obtaining semantically correct answers from a database that may be inconsistent with respect to its integrity constraints. In this work we formalize the notion of…

Databases · Computer Science 2011-06-09 M. Andrea Rodríguez , Leopoldo Bertossi , Monica Caniupan

Consistent query answering over a database that violates primary key constraints is a classical hard problem in database research that has been traditionally dealt with logic programming. However, the applicability of existing logic-based…

Artificial Intelligence · Computer Science 2015-07-23 Marco Manna , Francesco Ricca , Giorgio Terracina

Continuous sign language recognition (SLR) aims to translate a signing sequence into a sentence. It is very challenging as sign language is rich in vocabulary, while many among them contain similar gestures and motions. Moreover, it is…

Computer Vision and Pattern Recognition · Computer Science 2019-08-06 Zhaoyang Yang , Zhenmei Shi , Xiaoyong Shen , Yu-Wing Tai

In this paper, we propose a structured Robust Adaptive Dic-tionary Pair Learning (RA-DPL) framework for the discrim-inative sparse representation learning. To achieve powerful representation ability of the available samples, the setting of…

Computer Vision and Pattern Recognition · Computer Science 2019-11-21 Yulin Sun , Zhao Zhang , Weiming Jiang , Zheng Zhang , Li Zhang , Shuicheng Yan , Meng Wang
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