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Found 27 papers, 7 papers with code
LayerConnect: Hypernetwork-Assisted Inter-Layer Connector to Enhance Parameter Efficiency
Pre-trained Language Models (PLMs) are the cornerstone of the modern Natural Language Processing (NLP).
MIRTT: Learning Multimodal Interaction Representations from Trilinear Transformers for Visual Question Answering
On the other hand, trilinear models such as the CTI model efficiently utilize the inter-modality information between answers, questions, and images, while ignoring intra-modality information.
Evaluating the Effects of Embedding with Speaker Identity Information in Dialogue Summarization
Automatic dialogue summarization is a task used to succinctly summarize a dialogue transcript while correctly linking the speakers and their speech, which distinguishes this task from a conventional document summarization.
Decoy Effect In Search Interaction: Understanding User Behavior and Measuring System Vulnerability
This study examines the decoy effect's underexplored influence on user search interactions and methods for measuring information retrieval (IR) systems' vulnerability to this effect.
Decoy Effect in Search Interaction: A Pilot Study
In recent years, the influence of cognitive effects and biases on users' thinking, behaving, and decision-making has garnered increasing attention in the field of interactive information retrieval.
EALM: Introducing Multidimensional Ethical Alignment in Conversational Information Retrieval
Artificial intelligence (AI) technologies should adhere to human norms to better serve our society and avoid disseminating harmful or misleading information, particularly in Conversational Information Retrieval (CIR).
Open-Domain Dialogue Quality Evaluation: Deriving Nugget-level Scores from Turn-level Scores
Existing dialogue quality evaluation systems can return a score for a given system turn from a particular viewpoint, e. g., engagingness.
Towards Consistency Filtering-Free Unsupervised Learning for Dense Retrieval
In addition, consistency filtering often struggles to identify retrieval intentions and recognize query and corpus distributions in a target domain.
A Meta-Evaluation of C/W/L/A Metrics: System Ranking Similarity, System Ranking Consistency and Discriminative Power
In this study, we investigate the statistical stability of C/W/L/A metrics from the perspective of: (1) the system ranking similarity among aggregations, (2) the system ranking consistency of aggregations and (3) the discriminative power of aggregations.
SWAN: A Generic Framework for Auditing Textual Conversational Systems
We present a simple and generic framework for auditing a given textual conversational system, given some samples of its conversation sessions as its input.
ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models
Personalized content-based recommender systems have become indispensable tools for users to navigate through the vast amount of content available on platforms like daily news websites and book recommendation services.
NER-to-MRC: Named-Entity Recognition Completely Solving as Machine Reading Comprehension
Named-entity recognition (NER) detects texts with predefined semantic labels and is an essential building block for natural language processing (NLP).
Relevance Assessments for Web Search Evaluation: Should We Randomise or Prioritise the Pooled Documents? (CORRECTED VERSION)
In the context of depth-$k$ pooling for constructing web search test collections, we compare two approaches to ordering pooled documents for relevance assessors: the prioritisation strategy (PRI) used widely at NTCIR, and the simple randomisation strategy (RND).
Corrected Evaluation Results of the NTCIR WWW-2, WWW-3, and WWW-4 English Subtasks
The noise is due to a fatal bug in the backend of our relevance assessment interface.
Zero-Shot Learners for Natural Language Understanding via a Unified Multiple Choice Perspective
We propose a new paradigm for zero-shot learners that is format agnostic, i. e., it is compatible with any format and applicable to a list of language tasks, such as text classification, commonsense reasoning, coreference resolution, and sentiment analysis.
MAP: Multimodal Uncertainty-Aware Vision-Language Pre-training Model
Multimodal semantic understanding often has to deal with uncertainty, which means the obtained messages tend to refer to multiple targets.
On Variants of Root Normalised Order-aware Divergence and a Divergence based on Kendall's Tau
More specifically, the present study defines and evaluates, in addition to the quantification measures considered earlier, a few variants of an ordinal quantification measure called Root Normalised Order-aware Divergence (RNOD), as well as a measure which we call Divergence based on Kendall's $\tau$ (DNKT).
A Versatile Framework for Evaluating Ranked Lists in terms of Group Fairness and Relevance
We present a simple and versatile framework for evaluating ranked lists in terms of group fairness and relevance, where the groups (i. e., possible attribute values) can be either nominal or ordinal in nature.
AxIoU: An Axiomatically Justified Measure for Video Moment Retrieval
First, it is rank-insensitive: It ignores the rank positions of successfully localised moments in the top-$K$ ranked list by treating the list as a set.
Evaluating Evaluation Measures for Ordinal Classification and Ordinal Quantification
Ordinal Quantification (OQ) is a related task where the gold data is a distribution over ordinal classes, and the system is required to estimate this distribution.
Scalable Personalised Item Ranking through Parametric Density Estimation
However, such methods have two main drawbacks particularly in large-scale applications; (1) the pairwise approach is severely inefficient due to the quadratic computational cost; and (2) even recent model-based samplers (e. g. IRGAN) cannot achieve practical efficiency due to the training of an extra model.
DCH-2: A Parallel Customer-Helpdesk Dialogue Corpus with Distributions of Annotators' Labels
We introduce a data set called DCH-2, which contains 4, 390 real customer-helpdesk dialogues in Chinese and their English translations.
A Siamese CNN Architecture for Learning Chinese Sentence Similarity
This paper presents a deep neural architecture which applies the siamese convolutional neural network sharing model parameters for learning a semantic similarity metric between two sentences.
How to Measure the Reproducibility of System-oriented IR Experiments
Replicability and reproducibility of experimental results are primary concerns in all the areas of science and IR is not an exception.
Composing a Picture Book by Automatic Story Understanding and Visualization
Pictures can enrich storytelling experiences.
RSL19BD at DBDC4: Ensemble of Decision Tree-based and LSTM-based Models
RSL19BD (Waseda University Sakai Laboratory) participated in the Fourth Dialogue Breakdown Detection Challenge (DBDC4) and submitted five runs to both English and Japanese subtasks.
Graded Relevance Assessments and Graded Relevance Measures of NTCIR: A Survey of the First Twenty Years
NTCIR was the first large-scale IR evaluation conference to construct test collections with graded relevance assessments: the NTCIR-1 test collections from 1998 already featured relevant and partially relevant documents.
