Search Results for author:
Found 9 papers, 2 papers with code
Understanding LLM Development Through Longitudinal Study: Insights from the Open Ko-LLM Leaderboard
This paper conducts a longitudinal study over eleven months to address the limitations of prior research on the Open Ko-LLM Leaderboard, which have relied on empirical studies with restricted observation periods of only five months.
Open Ko-LLM Leaderboard: Evaluating Large Language Models in Korean with Ko-H5 Benchmark
This paper introduces the Open Ko-LLM Leaderboard and the Ko-H5 Benchmark as vital tools for evaluating Large Language Models (LLMs) in Korean.
SAAS: Solving Ability Amplification Strategy for Enhanced Mathematical Reasoning in Large Language Models
We focus on integrating the Chain-of-Thought (CoT) and the Program-of-Thought (PoT) learning, hypothesizing that prioritizing the learning of mathematical reasoning ability is helpful for the amplification of problem-solving ability.
sDPO: Don't Use Your Data All at Once
As development of large language models (LLM) progresses, aligning them with human preferences has become increasingly important.
Beyond the Contact: Discovering Comprehensive Affordance for 3D Objects from Pre-trained 2D Diffusion Models
To construct the distribution, we present a novel pipeline that synthesizes diverse and realistic 3D HOI samples given any 3D object mesh.
SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling
We introduce SOLAR 10. 7B, a large language model (LLM) with 10. 7 billion parameters, demonstrating superior performance in various natural language processing (NLP) tasks.
Lightweight Boosting Models for User Response Prediction Using Adversarial Validation
The ACM RecSys Challenge 2023, organized by ShareChat, aims to predict the probability of the app being installed.
Text2Scene: Text-driven Indoor Scene Stylization with Part-aware Details
We propose Text2Scene, a method to automatically create realistic textures for virtual scenes composed of multiple objects.
Real-Time Shape Tracking of Facial Landmarks
In this paper, we propose a method that can track the exact shape of facial landmarks in real-time by combining a deep learning technique and a point tracker.
