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Found 25 papers, 7 papers with code
Monotonic Paraphrasing Improves Generalization of Language Model Prompting
In this paper, we propose monotonic paraphrasing (MonoPara), an end-to-end decoding strategy that paraphrases given prompts or instructions into their lower perplexity counterparts based on an ensemble of a paraphrase LM for prompt (or instruction) rewriting, and a target LM (i. e. the prompt or instruction executor) that constrains the generation for lower perplexity.
An Effective Index for Truss-based Community Search on Large Directed Graphs
Community search is a derivative of community detection that enables online and personalized discovery of communities and has found extensive applications in massive real-world networks.
Fast Butterfly-Core Community Search For Large Labeled Graphs
Community Search (CS) aims to identify densely interconnected subgraphs corresponding to query vertices within a graph.
A Two-Stage Multimodal Emotion Recognition Model Based on Graph Contrastive Learning
To address the above issues, we propose a two-stage emotion recognition model based on graph contrastive learning (TS-GCL).
Adversarial Representation with Intra-Modal and Inter-Modal Graph Contrastive Learning for Multimodal Emotion Recognition
However, the existing feature fusion methods have usually mapped the features of different modalities into the same feature space for information fusion, which can not eliminate the heterogeneity between different modalities.
DER-GCN: Dialogue and Event Relation-Aware Graph Convolutional Neural Network for Multimodal Dialogue Emotion Recognition
Specifically, we construct a weighted multi-relationship graph to simultaneously capture the dependencies between speakers and event relations in a dialogue.
Deep Imbalanced Learning for Multimodal Emotion Recognition in Conversations
The main task of Multimodal Emotion Recognition in Conversations (MERC) is to identify the emotions in modalities, e. g., text, audio, image and video, which is a significant development direction for realizing machine intelligence.
A Comprehensive Survey on Multi-modal Conversational Emotion Recognition with Deep Learning
Unlike the traditional single-utterance multi-modal emotion recognition or single-modal conversation emotion recognition, MCER is a more challenging problem that needs to deal with more complex emotional interaction relationships.
Graph Information Bottleneck for Remote Sensing Segmentation
Furthermore, this paper innovatively introduces information bottleneck theory into graph contrastive learning to maximize task-related information while minimizing task-independent redundant information.
CZL-CIAE: CLIP-driven Zero-shot Learning for Correcting Inverse Age Estimation
Zero-shot age estimation aims to learn feature information about age from input images and make inferences about a given person's image or video frame without specific sample data.
Safety Guaranteed Control for Spacecraft Inspection Mission
In order to address this issue, we propose a control strategy based on control barrier functions, summarized as "safety check on kinematics" and "velocity tracking on dynamics" approach.
Adaptive Compatible Performance Control for Spacecraft Attitude Control under Motion Constraints with Guaranteed Accuracy
To tackle this problem, we propose a modified framework called Compatible Performance Control (CPC), which integrates the Prescribed Performance Control (PPC) scheme with a contradiction detection and alleviation strategy.
Composite Triggered Intermittent Control for Constrained Spacecraft Attitude Tracking
Further, the basic intermittent attitude controller is extended to a "constrained version" by introducing a strictly bounded virtual control law and an input saturation compensation auxiliary system.
Event-Triggered Intermittent Prescribed Performance Control for Spacecraft Attitude Reorientation
The prescribed performance control (PPC) scheme is often employed for the control with guaranteed performance.
Robust Control For Spacecraft Attitude Tracking Under Multiple Physical Limitations with Guaranteed Performance
Based on the proposed structure, a backstepping controller is developed accordingly using a double-layer PPC framework.
Spacecraft Attitude Pointing Control under Pointing Forbidden Constraints with Guaranteed Accuracy
To resolve this problem, a switching controller structure is proposed in this paper based on the reduced-attitude representation, fusing the artificial potential field (APF) methodology and the Prescribed Performance Control (PPC) scheme together.
Controllable Text Generation with Neurally-Decomposed Oracle
We propose a general and efficient framework to control auto-regressive generation models with NeurAlly-Decomposed Oracle (NADO).
On the Paradox of Learning to Reason from Data
Logical reasoning is needed in a wide range of NLP tasks.
GEMNET: Effective Gated Gazetteer Representations for Recognizing Complex Entities in Low-context Input
We propose GEMNET, a novel approach for gazetteer knowledge integration, including (1) a flexible Contextual Gazetteer Representation (CGR) encoder that can be fused with any word-level model; and (2) a Mixture-of- Experts gating network that overcomes the feature overuse issue by learning to conditionally combine the context and gazetteer features, instead of assigning them fixed weights.
InsNet: An Efficient, Flexible, and Performant Insertion-based Text Generation Model
We propose InsNet, an expressive insertion-based text generator with efficient training and flexible decoding (parallel or sequential).
An Integer Linear Programming Framework for Mining Constraints from Data
This raises a question -- \emph{can we mine constraints and rules from data based on a learning algorithm?}
Mitigating Gender Bias Amplification in Distribution by Posterior Regularization
With little performance loss, our method can almost remove the bias amplification in the distribution.
On the Robustness of Language Encoders against Grammatical Errors
We conduct a thorough study to diagnose the behaviors of pre-trained language encoders (ELMo, BERT, and RoBERTa) when confronted with natural grammatical errors.
SentiBERT: A Transferable Transformer-Based Architecture for Compositional Sentiment Semantics
We propose SentiBERT, a variant of BERT that effectively captures compositional sentiment semantics.
Target Language-Aware Constrained Inference for Cross-lingual Dependency Parsing
Experiments show that the Lagrangian relaxation and posterior regularization inference improve the performances on 15 and 17 out of 19 target languages, respectively.
