InfiAgent-DABench: Evaluating Agents on Data Analysis Tasks
LLM-based agents face challenges in data analysis tasks, leading to the development of InfiAgent-DABench for evaluation.
State Machine of Thoughts: Enhancing Problem Solving with Past Reasoning Trajectories
이 논문은 과거 추론 궤적을 활용하여 문제 해결 능력을 향상시키는 State Machine of Thoughts (SMoT) 패러다임을 소개합니다.
PROMETHEUS: Fine-Grained Evaluation Capability in Language Models
PROMETHEUS introduces fine-grained evaluation capabilities in language models, emphasizing the importance of open-source and reproducible models.
LLM4VV: Developing LLM-Driven Testsuite for Compiler Validation
Large language models (LLMs) are utilized to automatically generate tests for compiler validation, focusing on OpenACC implementations.
[SF]2M: Simulation-Free Schrödinger Bridges via Score and Flow Matching
[SF]2M is a simulation-free method that efficiently approximates Schrödinger bridges, outperforming existing methods in generative modeling and dynamic optimal transport.
HIFA: High-Fidelity Text-to-3D Generation with Advanced Diffusion Guidance at ICLR 2024
고품질 텍스트-3D 생성을 위한 고급 확산 가이드를 통한 HIFA 방법론 소개
M4: Multi-Generator, Multi-Domain, and Multi-Lingual Black-Box Machine-Generated Text Detection
Large language models have led to an increase in machine-generated content, raising concerns about potential misuse. This study focuses on creating automated systems to detect machine-generated texts and address misuse.
Unmasked Teacher: Training-Efficient Video Foundation Models
효율적인 비디오 기반 모델 훈련 방법 소개
OpenXAI: A Comprehensive Framework for Evaluating Post hoc Model Explanations
OpenXAI는 후속 모델 설명을 평가하기 위한 포괄적이고 확장 가능한 오픈 소스 프레임워크를 소개합니다.
SELMA: Improving Text-to-Image Models with SELMA Paradigm
SELMA introduces a novel paradigm to enhance the faithfulness of Text-to-Image models by fine-tuning on auto-generated datasets and merging skill-specific experts.
© 2024 by Linnk AI