Search Results for author:
Found 7 papers, 1 papers with code
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.
Zero-Shot Learning for the Primitives of 3D Affordance in General Objects
One of the major challenges in AI is teaching machines to precisely respond and utilize environmental functionalities, thereby achieving the affordance awareness that humans possess.
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.
