Top Conference Papers

INDICLLMSUITE: A Blueprint for Creating Pre-training and Fine-Tuning Datasets for Indian Languages

Every Bit Helps: Achieving the Optimal Distortion with a Few Queries

LINE: Large-scale Information Network Embedding

Factorizing Personalized Markov Chains for Next-Basket Recommendation

Topic-Sensitive PageRank

The Dataflow Model: A Practical Approach to Balancing Correctness, Latency, and Cost in Massive-Scale, Unbounded, Out-of-Order Data Processing

How Good Are Query Optimizers, Really?

Hadoop-GIS: A High Performance Spatial Data Warehousing System over MapReduce

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Artificial Hivemind: The Open-Ended Homogeneity of Language Models (and Beyond)

Sequence to Sequence Learning with Neural Networks

Generative Adversarial Nets

The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models

Asynchronous Methods for Deep Reinforcement Learning

Variational Inference with Normalizing Flows

Trust Region Policy Optimization

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition

UNSUPERVISED REPRESENTATION LEARNING WITH DEEP CONVOLUTIONAL GENERATIVE ADVERSARIAL NETWORKS

CONTINUOUS CONTROL WITH DEEP REINFORCEMENT LEARNING

NEURAL MACHINE TRANSLATION BY JOINTLY LEARNING TO ALIGN AND TRANSLATE

ADAM: A METHOD FOR STOCHASTIC OPTIMIZATION

ALPHAEDIT: NULL-SPACE CONSTRAINED KNOWLEDGE EDITING FOR LANGUAGE MODELS

Intriguing properties of neural networks

Auto-Encoding Variational Bayes

Fast R-CNN

Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

SSD: Single Shot MultiBox Detector

Perceptual Losses for Real-Time Style Transfer and Super-Resolution