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Found 18 papers, 9 papers with code
A Multi-modal Personality Prediction System
Automatic prediction of personality traits has many real-life applications, e. g., in forensics, recommender systems, personalized services etc..
Personality Trait Recognition by Face
Recommendation Systems
Agri-GNN: A Novel Genotypic-Topological Graph Neural Network Framework Built on GraphSAGE for Optimized Yield Prediction
Agriculture, as the cornerstone of human civilization, constantly seeks to integrate technology for enhanced productivity and sustainability.
AutoMix: Automatically Mixing Language Models
Large language models (LLMs) are now available from cloud API providers in various sizes and configurations.
How FaR Are Large Language Models From Agents with Theory-of-Mind?
We propose a new evaluation paradigm for large language models (LLMs): Thinking for Doing (T4D), which requires models to connect inferences about others' mental states to actions in social scenarios.
The Growth of E-Bike Use: A Machine Learning Approach
Using an ARIMA model, a supervised machine-learning algorithm, we predicted the growth of e-bike sales in the U. S. Our model, trained on historical sales data from January 2006 to December 2022, projected sales of 1. 3 million units in 2025 and 2. 113 million units in 2028.
The Value of Chess Squares
We propose a neural network-based approach to calculate the value of a chess square-piece combination.
Using Monte Carlo Methods for Retirement Simulations
Retirement prediction helps individuals and institutions make informed financial, lifestyle, and workforce decisions based on estimated retirement portfolios.
Inter Subject Emotion Recognition Using Spatio-Temporal Features From EEG Signal
We used the Dataset on Emotion using Naturalistic Stimuli (DENS) dataset.
PRESTO: A Multilingual Dataset for Parsing Realistic Task-Oriented Dialogs
Research interest in task-oriented dialogs has increased as systems such as Google Assistant, Alexa and Siri have become ubiquitous in everyday life.
Efficient Encoders for Streaming Sequence Tagging
A naive application of state-of-the-art bidirectional encoders for streaming sequence tagging would require encoding each token from scratch for each new token in an incremental streaming input (like transcribed speech).
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
BIG-bench focuses on tasks that are believed to be beyond the capabilities of current language models.
Discovering Intrinsic Reward with Contrastive Random Walk
The aim of this paper is to demonstrate the efficacy of using Contrastive Random Walk as a curiosity method to achieve faster convergence to the optimal policy. Contrastive Random Walk defines the transition matrix of a random walk with the help of neural networks.
Improving Top-K Decoding for Non-Autoregressive Semantic Parsing via Intent Conditioning
As the top-level intent largely governs the syntax and semantics of a parse, the intent conditioning allows the model to better control beam search and improves the quality and diversity of top-k outputs.
TableFormer: Robust Transformer Modeling for Table-Text Encoding
Existing models for table understanding require linearization of the table structure, where row or column order is encoded as an unwanted bias.
Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering
Disfluencies is an under-studied topic in NLP, even though it is ubiquitous in human conversation.
TIMEDIAL: Temporal Commonsense Reasoning in Dialog
In this paper, we present the first study to investigate pre-trained LMs for their temporal reasoning capabilities in dialogs by introducing a new task and a crowd-sourced English challenge set, TIMEDIAL.
Effective Use of Transformer Networks for Entity Tracking
Tracking entities in procedural language requires understanding the transformations arising from actions on entities as well as those entities' interactions.
Tracking Discrete and Continuous Entity State for Process Understanding
The global discrete state structure is explicitly modeled with a neural CRF over the changing hidden representation of the entity.
Ranked #2 on
Procedural Text Understanding
on ProPara
