# Proceedings of the AAAI Conference on Artificial Intelligence

**Type:** Journals  
**Canonical URL:** https://scholariq.org/journals/proceedings-of-the-aaai-conference-on-artificial-intelligence/

## Facts

| Field | Value |
| --- | --- |
| Open Access | true |
| ISSN-L | 2159-5399 |
| ISSNs | 2159-5399,2374-3468 |
| OpenAlex ID | https://openalex.org/S4210191458 |
| Publisher | Association for the Advancement of Artificial Intelligence |

## Journal papers

Showing 12 of 24.

- [Spatiotemporal Multi-Graph Convolution Network for Ride-Hailing Demand Forecasting](https://scholariq.org/papers/spatiotemporal-multi-graph-convolution-network-for-ride-hailing-demand/)
- [Long Text Generation via Adversarial Training with Leaked Information](https://scholariq.org/papers/long-text-generation-via-adversarial-training-with-leaked-information/)
- [Where to Go Next: Modeling Long- and Short-Term User Preferences for Point-of-Interest Recommendation](https://scholariq.org/papers/where-to-go-next-modeling-long-and-short-term-user-preferences-for-point-of/)
- [Cross-Modality Paired-Images Generation for RGB-Infrared Person Re-Identification](https://scholariq.org/papers/cross-modality-paired-images-generation-for-rgb-infrared-person-re/)
- [Where to Go Next: A Spatio-Temporal Gated Network for Next POI Recommendation](https://scholariq.org/papers/where-to-go-next-a-spatio-temporal-gated-network-for-next-poi-recommendation/)
- [Multi-View Clustering in Latent Embedding Space](https://scholariq.org/papers/multi-view-clustering-in-latent-embedding-space/)
- [A Coarse-to-Fine Adaptive Network for Appearance-Based Gaze Estimation](https://scholariq.org/papers/a-coarse-to-fine-adaptive-network-for-appearance-based-gaze-estimation/)
- [Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning](https://scholariq.org/papers/contrastive-and-generative-graph-convolutional-networks-for-graph-based-semi/)
- [Listen, Attend, and Walk: Neural Mapping of Navigational Instructions to Action Sequences](https://scholariq.org/papers/listen-attend-and-walk-neural-mapping-of-navigational-instructions-to-action/)
- [Rolling-Unet: Revitalizing MLP’s Ability to Efficiently Extract Long-Distance Dependencies for Medical Image Segmentation](https://scholariq.org/papers/rolling-unet-revitalizing-mlp-s-ability-to-efficiently-extract-long-distance/)
- [Coherent Dialogue with Attention-Based Language Models](https://scholariq.org/papers/coherent-dialogue-with-attention-based-language-models/)
- [Mitigating Political Bias in Language Models through Reinforced Calibration](https://scholariq.org/papers/mitigating-political-bias-in-language-models-through-reinforced-calibration/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.