On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,982 papers · 148 categories

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6 results for “Position-aware”

Position-aware Graph Neural Networkscs.LG

P-GNNs learn node embeddings considering node positions in graphs.

problem Capturing node positions in graph structures.

method Samples anchor nodes, computes distances, and learns weighted aggregation.

result P-GNNs outperform state-of-the-art GNNs in link prediction and community detection.

Graph Neural Networks Position-aware Node Embeddings Link Prediction Community Detection

2019-06-11abs ↗pdf ↗

GraphReach: Position-Aware Graph Neural Network using Reachability Estimationscs.SI

GraphReach improves GNN performance by incorporating node positions.

problem Existing GNNs fail to capture node positions, leading to inaccurate predictions.

method GraphReach uses reachability estimations from anchor nodes to capture global node positions.

result GraphReach achieves up to 40% relative improvement in accuracy compared to state-of-the-art GNNs.

Graph Neural Networks Position-Aware Reachability Estimations NP-hard Greedy Heuristic

2020-08-19abs ↗pdf ↗

Position-Aware Convolutional Networks for Traffic Predictioncs.LG

Paper proposes a neural network to improve traffic flow forecasting.

problem Forecasting future traffic flow distribution in an area.

method Position-aware convolutional neural network integrating data features and position information.

result Our approach outperforms previous methods even with fewer data sources.

traffic prediction neural networks position embedding convolutional neural networks spatial-temporal relations

2019-04-12abs ↗pdf ↗

Generalized Stock Price Prediction for Multiple Stocks Combined with News Fusionq-fin.ST

This paper predicts stock prices using LLMs and news embeddings.

problem Predicting stock prices with high accuracy and relevance.

method Integrates LLMs with stock name embeddings and attention mechanisms for news filtering.

result Reduces MAE by 7.11% compared to baseline.

stock price prediction LLMs news fusion attention mechanisms embedding

2026-03-08abs ↗pdf ↗

DRFormer: Multi-Scale Transformer Utilizing Diverse Receptive Fields for Long Time-Series Forecastingcs.LG

DRFormer uses dynamic tokenization and multi-scale transformer to forecast long time series.

problem Forecasting long-term time series data across diverse scales.

method Dynamic tokenizer, multi-scale transformer, dynamic sparse learning, rotary position encoding.

result DRFormer outperforms existing methods in forecasting accuracy.

time series forecasting transformer model dynamic tokenization multi-scale sparse learning

2024-08-05abs ↗pdf ↗

Learning in Position-Aware Multinomial Logit Bandits: From Multiplicative to General Position Effectscs.LG

Study dynamic assortment and positioning of products with varying display effects.

problem Dynamic assortment and positioning of products with varying display effects.

method Design round-based learning algorithms for both multiplicative and general position effects models, and develop efficient subroutines for optimization.

result First regret-optimal characterization for both models, with matching upper and lower bounds.

Multinomial Logit Position Effects Dynamic Assortment Regret Minimization Display Effects

2026-05-17abs ↗pdf ↗