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Found 30 papers, 5 papers with code
KG-TRICK: Unifying Textual and Relational Information Completion of Knowledge for Multilingual Knowledge Graphs
Multilingual knowledge graphs (KGs) provide high-quality relational and textual information for various NLP applications, but they are often incomplete, especially in non-English languages.
Enhancing Discoverability in Enterprise Conversational Systems with Proactive Question Suggestions
Enterprise conversational AI systems are becoming increasingly popular to assist users in completing daily tasks such as those in marketing and customer management.
Heavy-tailed Contamination is Easier than Adversarial Contamination
First, we prove that any adversarially robust estimator is also resilient to heavy-tailed outliers for any statistical estimation problem with i. i. d data.
FunctionChat-Bench: Comprehensive Evaluation of Language Models' Generative Capabilities in Korean Tool-use Dialogs
This study investigates language models' generative capabilities in tool-use dialogs.
Towards Cross-Cultural Machine Translation with Retrieval-Augmented Generation from Multilingual Knowledge Graphs
Translating text that contains entity names is a challenging task, as cultural-related references can vary significantly across languages.
Model-in-the-Loop (MILO): Accelerating Multimodal AI Data Annotation with LLMs
The growing demand for AI training data has transformed data annotation into a global industry, but traditional approaches relying on human annotators are often time-consuming, labor-intensive, and prone to inconsistent quality.
RETAIN: Interactive Tool for Regression Testing Guided LLM Migration
To bridge this gap, we introduce RETAIN (REgression Testing guided LLM migrAtIoN), a tool designed explicitly for regression testing in LLM Migrations.
MuRAR: A Simple and Effective Multimodal Retrieval and Answer Refinement Framework for Multimodal Question Answering
Recent advancements in retrieval-augmented generation (RAG) have demonstrated impressive performance in the question-answering (QA) task.
ConvKGYarn: Spinning Configurable and Scalable Conversational Knowledge Graph QA datasets with Large Language Models
The rapid advancement of Large Language Models (LLMs) and conversational assistants necessitates dynamic, scalable, and configurable conversational datasets for training and evaluation.
Increasing Coverage and Precision of Textual Information in Multilingual Knowledge Graphs
Recent work in Natural Language Processing and Computer Vision has been using textual information -- e. g., entity names and descriptions -- available in knowledge graphs to ground neural models to high-quality structured data.
SmartBook: AI-Assisted Situation Report Generation for Intelligence Analysts
Timely and comprehensive understanding of emerging events is crucial for effective decision-making; automating situation report generation can significantly reduce the time, effort, and cost for intelligence analysts.
From Pseudorandomness to Multi-Group Fairness and Back
We identify and explore connections between the recent literature on multi-group fairness for prediction algorithms and the pseudorandomness notions of leakage-resilience and graph regularity.
AuraSense: Robot Collision Avoidance by Full Surface Proximity Detection
In this paper, we introduce the phenomenon of the Leaky Surface Wave (LSW), a novel sensing modality, and present AuraSense, a proximity detection system using the LSW.
Online Minimax Multiobjective Optimization: Multicalibeating and Other Applications
We introduce a simple but general online learning framework in which a learner plays against an adversary in a vector-valued game that changes every round.
Answering Chinese Elementary School Social Study Multiple Choice Questions
We present a novel approach to answer the Chinese elementary school Social Study Multiple Choice questions.
Auxiliary Sequence Labeling Tasks for Disfluency Detection
Existing works for disfluency detection have focused on designing a single objective only for disfluency detection, while auxiliary objectives utilizing linguistic information of a word such as named entity or part-of-speech information can be effective.
Experiments in Extractive Summarization: Integer Linear Programming, Term/Sentence Scoring, and Title-driven Models
In this paper, we revisit the challenging problem of unsupervised single-document summarization and study the following aspects: Integer linear programming (ILP) based algorithms, Parameterized normalization of term and sentence scores, and Title-driven approaches for summarization.
Reference and Document Aware Semantic Evaluation Methods for Korean Language Summarization
In this paper, we propose evaluation metrics that reflect semantic meanings of a reference summary and the original document, Reference and Document Aware Semantic Score (RDASS).
Robotic Grasping through Combined image-Based Grasp Proposal and 3D Reconstruction
We present a novel approach to robotic grasp planning using both a learned grasp proposal network and a learned 3D shape reconstruction network.
Robotics
Cephalometric Landmark Detection by Attentive Feature Pyramid Fusion and Regression-Voting
Marking anatomical landmarks in cephalometric radiography is a critical operation in cephalometric analysis.
QXplore: Q-Learning Exploration by Maximizing Temporal Difference Error
We implement the objective with an adversarial Q-learning method in which Q and Qx are the action-value functions for extrinsic and secondary rewards, respectively.
Cephalometric Landmark Detection by AttentiveFeature Pyramid Fusion and Regression-Voting
Marking anatomical landmarks in cephalometric radiography is a critical operation in cephalometric analysis.
Newswire versus Social Media for Disaster Response and Recovery
In a disaster situation, first responders need to quickly acquire situational awareness and prioritize response based on the need, resources available and impact.
Reward Prediction Error as an Exploration Objective in Deep RL
We then propose a deep reinforcement learning method, QXplore, which exploits the temporal difference error of a Q-function to solve hard exploration tasks in high-dimensional MDPs.
Q-Learning for Continuous Actions with Cross-Entropy Guided Policies
CGP aims to combine the stability and performance of iterative sampling policies with the low computational cost of a policy network.
Identifying Reference Spans: Topic Modeling and Word Embeddings help IR
The CL-SciSumm 2016 shared task introduced an interesting problem: given a document D and a piece of text that cites D, how do we identify the text spans of D being referenced by the piece of text?
Extractive Summarization: Limits, Compression, Generalized Model and Heuristics
Due to its promise to alleviate information overload, text summarization has attracted the attention of many researchers.
The Stan Math Library: Reverse-Mode Automatic Differentiation in C++
As computational challenges in optimization and statistical inference grow ever harder, algorithms that utilize derivatives are becoming increasingly more important.
Mathematical Software G.1.0; G.1.3; G.1.4; F.2.1
