A recent trend in multimodal retrieval is related to postprocessing test set results via the dual-softmax loss (DSL). While this approach can bring significant improvements, it usually presumes that an entire matrix of test samples is available as DSL ...

Given a textual sentence provided by a user, the Temporal Language Grounding (TLG) task is defined as the process of finding a semantically relevant video moment or clip from an untrimmed video. In recent years, localization-based TLG methods have been ...

The information retrieval community has observed significant performance improvements over various tasks due to the introduction of neural architectures. However, such improvements do not necessarily seem to have happened uniformly across a range of ...

The purpose of audio-text retrieval is to learn a cross-modal similarity function between audio and text, enabling a given audio/text to find similar text/audio from a candidate set. Recent audio-text retrieval models aggregate multi-modal features into ...

Data collection and mining is a crucial bottleneck for cross-lingual information retrieval (CLIR). While previous works used machine translation and iterative training, we present a novel approach to cross-lingual pretraining called LAPCA (language-...

Advancements in text-guided diffusion models have allowed for the creation of visually appealing images similar to those created by professional artists. The effectiveness of these models depends on the composition of the textual description, known as ...

The rise in loosely-structured data available through text, images, and other modalities has called for new ways of querying them. Multimedia Information Retrieval has filled this gap and has witnessed exciting progress in recent years. Tasks such as ...

eCommerce Information Retrieval (IR) is receiving increasing attention in the academic literature and is an essential component of some of the largest web sites (e.g. Airbnb, Alibaba, Amazon, eBay, Facebook, Flipkart, Lowes's, Taobao, Target). SIGIR has ...

Knowledge discovery from unstructured data, including business documents, web content, and news articles, has been a key AI challenge for the financial services industry. Comprehending these corpora and discovering knowledge from them, which could be ...

LongEval-Retrieval is a Web document retrieval benchmark that focuses on continuous retrieval evaluation. This test collection is intended to be used to study the temporal persistence of Information Retrieval systems and will be used as the test ...

Given a text query on a controversial topic, the task of Image Retrieval for Argumentation is to rank images according to how well they can be used to support a discussion on the topic. An important subtask therein is to determine the stance of the ...

The IARPA BETTER (Better Extraction from Text Through Enhanced Retrieval) program held three evaluations of information retrieval (IR) and information extraction (IE). For both tasks, the only training data available was in English, but systems had to ...

This paper presents the AToMiC (Authoring Tools for Multi media Content) dataset, designed to advance research in image/text cross-modal retrieval. While vision--language pretrained transformers have led to significant improvements in retrieval ...

Student modeling, the task of inferring a student's learning characteristics through their interactions with coursework, is a fundamental issue in intelligent education. Although the recent attempts from knowledge tracing and cognitive diagnosis propose ...

While there are many test collections for Cross-Language Information Retrieval (CLIR), none of the large public test collections focus on short informal text documents. This paper introduces a new pair of CLIR test collections with millions of Chinese or ...

Despite recent advances in information retrieval and natural language processing, rhetorical devices that exploit ambiguity or subvert linguistic rules remain a challenge for such systems. However, corpus-based analysis of wordplay has been a perennial ...

Users in consumption domains, like music, are often able to more efficiently provide preferences over a set of items (e.g. a playlist or radio) than over single items (e.g. songs). Unfortunately, this is an underexplored area of research, with most ...

We propose end-to-end multimodal fact-checking and explanation generation, where the input is a claim and a large collection of web sources, including articles, images, videos, and tweets, and the goal is to assess the truthfulness of the claim by ...

Graph-structured diagrams, such as enterprise ownership charts or management hierarchies, are a challenging medium for deep learning models as they not only require the capacity to model language and spatial relations but also the topology of links ...

Illegal live-streaming identification, which aims to help live-streaming platforms immediately recognize the illegal behaviors in the live-streaming, such as selling precious and endangered animals, plays a crucial role in purifying the network ...