Related papers: Everyone is a Curator: Human-Assisted Preservation…

With the spread of robots in unstructured, dynamic environments, the topic of path replanning has gained importance in the robotics community. Although the number of replanning strategies has significantly increased, there is a lack of…

We present Regularized Linear Embedding (RLE), a novel method that projects a collection of linked documents (e.g. citation network) into a pretrained word embedding space. In addition to the textual content, we leverage a matrix of…

Search is a key service within constraint programming systems, and it demands the restoration of previously accessed states during the exploration of a search tree. Restoration proceeds either bottom-up within the tree to roll back…

Information retrieval (IR) in dynamic data streams is a crucial task, as shifts in data distribution degrade the performance of AI-powered IR systems. To mitigate this issue, memory-based continual learning has been widely adopted for IR.…

Annotation graphs and annotation servers offer infrastructure to support the analysis of human language resources in the form of time-series data such as text, audio and video. This paper outlines areas of common need among empirical…

Considering the limited internal parametric knowledge, retrieval-augmented generation (RAG) has been widely used to extend the knowledge scope of large language models (LLMs). Despite the extensive efforts on RAG research, in existing…

The preservation of cultural heritage faces growing challenges from climate change, tourism pressure, and limited conservation resources. Existing monitoring solutions are often cost-prohibitive, proprietary, and inflexible, leaving many…

Archives play a crucial role in the construction and advancement of society. Humans place a great deal of trust in archives and depend on them to craft public policies and to preserve languages, cultures, self-identity, views and values.…

How do humans recognize an object in a piece of video? Due to the deteriorated quality of single frame, it may be hard for people to identify an occluded object in this frame by just utilizing information within one image. We argue that…

The idea of reusing information from previously learned tasks (source tasks) for the learning of new tasks (target tasks) has the potential to significantly improve the sample efficiency reinforcement learning agents. In this work, we…

Reminiscence activities, which involve recalling and sharing past experiences, have proven beneficial for improving cognitive function, mood, and overall well-being. However, urbanization has led to the disappearance of familiar…

Recent advancements in LLM-powered agents have demonstrated significant potential in generating human-like responses; however, they continue to face challenges in maintaining long-term interactions within complex environments, primarily due…

In this study, we aim to incorporate the expertise of anonymous curators into a token-curated registry (TCR), a decentralized recommender system for collecting a list of high-quality content. This registry is important, because previous…

OpenStreetMap (OSM) is currently the richest publicly available information source on geographic entities (e.g., buildings and roads) worldwide. However, using OSM entities in machine learning models and other applications is challenging…

Recommender systems are increasingly successful in recommending personalized content to users. However, these systems often capitalize on popular content. There is also a continuous evolution of user interests that need to be captured, but…

Describing cultural heritage objects from the perspective of Linked Open Data (LOD) is not a trivial task. The process often requires not only choosing pertinent ontologies, but also developing new models that preserve the most information…

Retrieval augmented generation (RAG) has been widely adopted to help Large Language Models (LLMs) to process tasks involving long documents. However, existing retrieval models are not designed for long document retrieval and fail to address…

Real-world information needs require access to structurally diverse knowledge sources, from unstructured text and relational tables to knowledge graphs and property graphs. Existing retrievers, however, operate over one source at a time…

In our daily lives, organizing resources into a set of categories is a common task. Categorization becomes more useful as the collection of resources increases. Large collections of books, movies, and web pages, for instance, are cataloged…

Copious amounts of relevance judgments are necessary for the effective training and accurate evaluation of retrieval systems. Conventionally, these judgments are made by human assessors, rendering this process expensive and laborious. A…