Integrating contact-awareness into a soft snake robot and efficiently
co...
Federated Learning (FL) is a distributed machine learning technique that...
Electronic Bill (E-Bill) is a rucial negotiable instrument in the form o...
Text evaluation has historically posed significant challenges, often
dem...
In this work, we study a class of deception planning problems in which a...
Self-supervised learning (SSL) has shown promising results in various sp...
Weakly-supervised audio-visual video parsing (WS-AVVP) aims to localize ...
We introduce LyricWhiz, a robust, multilingual, and zero-shot automatic
...
Federated learning (FL), a privacy-preserving distributed machine learni...
The task of empowering large language models (LLMs) to accurately expres...
In the era of extensive intersection between art and Artificial Intellig...
Large language models (LLMs) with memory are computationally universal.
...
Self-supervised learning (SSL) has recently emerged as a promising parad...
Due to Multilingual Neural Machine Translation's (MNMT) capability of
ze...
Learned optimizers are a crucial component of meta-learning. Recent
adva...
Interactive Natural Language Processing (iNLP) has emerged as a novel
pa...
In this paper, we release a largest ever medical Question Answering (QA)...
The prompt-based learning paradigm, which bridges the gap between
pre-tr...
We present a new model for generating molecular data by combining discre...
Homophily principle, i.e. nodes with the same labels are more likely to ...
This paper studies temporal planning in probabilistic environments, mode...
Instruction tuning is widely recognized as a key technique for building
...
Language-Image Pre-training has demonstrated promising results on zero-s...
This paper is concerned with the optimal allocation of detection resourc...
New retrieval tasks have always been emerging, thus urging the developme...
This paper addresses the problem of enabling a robot to search for a sem...
This paper investigates the problem of synthesizing proactive defense sy...
As natural language processing (NLP) for gender bias becomes a significa...
Vision Transformers have shown great promise recently for many vision ta...
The deep learning community has witnessed an exponentially growing inter...
Federated learning seeks to address the issue of isolated data islands b...
Differential privacy (DP) provides a formal privacy guarantee that preve...
Incorporating large-scale pre-trained models with the prototypical neura...
Fairness has become a trending topic in natural language processing (NLP...
This paper details our participation in the Challenges and Applications ...
In this paper, we present our approach and empirical observations for
Ca...
Text editing, such as grammatical error correction, arises naturally fro...
This paper studies the deployment of joint moving target defense (MTD) a...
Preferences play a key role in determining what goals/constraints to sat...
In this paper, we study planning in stochastic systems, modeled as Marko...
In offline model-based optimization, we strive to maximize a black-box
o...
Intention deception involves computing a strategy which deceives the opp...
In this work, we present a learning-based goal-tracking control method f...
We consider the probabilistic planning problem for a defender (P1) who c...
Preferences play a key role in determining what goals/constraints to sat...
Mental health is a critical issue in modern society, and mental disorder...
Pre-trained language models (PLMs) have been the de facto paradigm for m...
Black-box optimization formulations for biological sequence design have ...
We propose pruning ternary quantization (PTQ), a simple, yet effective,
...
In recent years, the fast rise in number of studies on graph neural netw...