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Found 17 papers, 5 papers with code
Structural Realization with GGNNs
In this paper, we define an abstract task called structural realization that generates words given a prefix of words and a partial representation of a parse tree.
Sequence-level Large Language Model Training with Contrastive Preference Optimization
The next token prediction loss is the dominant self-supervised training objective for large language models and has achieved promising results in a variety of downstream tasks.
Role-Play Paradox in Large Language Models: Reasoning Performance Gains and Ethical Dilemmas
Role-play in large language models (LLMs) enhances their ability to generate contextually relevant and high-quality responses by simulating diverse cognitive perspectives.
MSDet: Receptive Field Enhanced Multiscale Detection for Tiny Pulmonary Nodule
Pulmonary nodules are critical indicators for the early diagnosis of lung cancer, making their detection essential for timely treatment.
LongRecipe: Recipe for Efficient Long Context Generalization in Large Language Models
Large language models (LLMs) face significant challenges in handling long-context tasks because of their limited effective context window size during pretraining, which restricts their ability to generalize over extended sequences.
MMREC: LLM Based Multi-Modal Recommender System
This surge in content presents unique challenges for designing effective recommender systems.
Data Imputation using Large Language Model to Accelerate Recommendation System
We evaluate our LLM-based imputation method across various tasks within the recommendation system domain, including single classification, multi-classification, and regression compared to traditional data imputation methods.
Exploring the Limitations of Large Language Models in Compositional Relation Reasoning
We present a comprehensive evaluation of large language models(LLMs)' ability to reason about composition relations through a benchmark encompassing 1, 500 test cases in English, designed to cover six distinct types of composition relations: Positional, Comparative, Personal, Mathematical, Identity, and Other.
Gender Bias in Large Language Models across Multiple Languages
We investigate the outputs of the GPT series of LLMs in various languages using our three measurement methods.
Large Language Models of Code Fail at Completing Code with Potential Bugs
We find that the presence of potential bugs significantly degrades the generation performance of the high-performing Code-LLMs.
Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion
To better solve this task, we query a program analyzer for information relevant to a given function call, and consider ways to provide the analyzer results to different code completion models during inference and training.
Code Prediction by Feeding Trees to Transformers
We provide comprehensive experimental evaluation of our proposal, along with alternative design choices, on a standard Python dataset, as well as on a Python corpus internal to Facebook.
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Generalizing Word Embeddings using Bag of Subwords
We approach the problem of generalizing pre-trained word embeddings beyond fixed-size vocabularies without using additional contextual information.
Neural-Augmented Static Analysis of Android Communication
We address the problem of discovering communication links between applications in the popular Android mobile operating system, an important problem for security and privacy in Android.
The Effect of Network Width on the Performance of Large-batch Training
Distributed implementations of mini-batch stochastic gradient descent (SGD) suffer from communication overheads, attributed to the high frequency of gradient updates inherent in small-batch training.
