Search Results for author:
Found 14 papers, 5 papers with code
From Generalist to Specialist: A Survey of Large Language Models for Chemistry
Large Language Models (LLMs) have significantly transformed our daily life and established a new paradigm in natural language processing (NLP).
Counterfactual Uncertainty Quantification of Factual Estimand of Efficacy from Before-and-After Treatment Repeated Measures Randomized Controlled Trials
The ideal estimand for comparing treatment $Rx$ with a control $C$ is the $\textit{counterfactual}$ efficacy $Rx:C$, the expected differential outcome between $Rx$ and $C$ if each patient were given $\textit{both}$.
Magnetic Preference Optimization: Achieving Last-iterate Convergence for Language Model Alignment
Self-play methods have demonstrated remarkable success in enhancing model capabilities across various domains.
AlignSum: Data Pyramid Hierarchical Fine-tuning for Aligning with Human Summarization Preference
This demonstrates that AlignSum significantly enhances the alignment of language models with human summarization preferences.
J2N -- Nominal Adjective Identification and its Application
This paper explores the challenges posed by nominal adjectives (NAs) in natural language processing (NLP) tasks, particularly in part-of-speech (POS) tagging.
Research on fusing topological data analysis with convolutional neural network
This method combines numerical distribution features captured by CNN with topological structure features captured by TDA to improve the feature learning and representation ability of CNN.
Reward Generalization in RLHF: A Topological Perspective
As a solution, we introduce a theoretical framework for investigating reward generalization in reinforcement learning from human feedback (RLHF), focusing on the topology of information flow at both macro and micro levels.
SciEval: A Multi-Level Large Language Model Evaluation Benchmark for Scientific Research
This design suffers from data leakage problem and lacks the evaluation of subjective Q/A ability.
Identifying outliers in astronomical images with unsupervised machine learning
For comparison, we construct three methods, which are built upon the k-nearest neighbors (KNN), Convolutional Auto-Encoder (CAE)+ KNN, and CAE + KNN + Attention Mechanism (attCAE KNN) separately.
AKB-48: A Real-World Articulated Object Knowledge Base
To bridge the gap, we present AKB-48: a large-scale Articulated object Knowledge Base which consists of 2, 037 real-world 3D articulated object models of 48 categories.
Shuffle Transformer with Feature Alignment for Video Face Parsing
This is a short technical report introducing the solution of the Team TCParser for Short-video Face Parsing Track of The 3rd Person in Context (PIC) Workshop and Challenge at CVPR 2021.
Deep-AIR: A Hybrid CNN-LSTM Framework for Air Quality Modeling in Metropolitan Cities
Our proposed framework creates 1x1 convolution layers to strengthen the learning of cross-feature spatial interaction between air pollution and important urban dynamic features, particularly road density, building density/height, and street canyon effect.
Evaluating the Discrimination Ability of Proper Multivariate Scoring Rules
Proper scoring rules are commonly applied to quantify the accuracy of distribution forecasts.
Methodology Statistical Finance Applications
A Further Study of Unsupervised Pre-training for Transformer Based Speech Recognition
In this paper, we conduct a further study on MPC and focus on three important aspects: the effect of pre-training data speaking style, its extension on streaming model, and how to better transfer learned knowledge from pre-training stage to downstream tasks.
