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Found 5 papers, 0 papers with code
Context-Enhanced Language Models for Generating Multi-Paper Citations
This research underscores the potential of harnessing LLMs for citation generation, opening a compelling avenue for exploring the intricate connections between scientific documents.
MM-PhyRLHF: Reinforcement Learning Framework for Multimodal Physics Question-Answering
We employ the LLaVA open-source model to answer multimodal physics MCQs and compare the performance with and without using RLHF.
KG-CTG: Citation Generation through Knowledge Graph-guided Large Language Models
Citation Text Generation (CTG) is a task in natural language processing (NLP) that aims to produce text that accurately cites or references a cited document within a source document.
MM-PhyQA: Multimodal Physics Question-Answering With Multi-Image CoT Prompting
While Large Language Models (LLMs) can achieve human-level performance in various tasks, they continue to face challenges when it comes to effectively tackling multi-step physics reasoning tasks.
Certified Zeroth-order Black-Box Defense with Robust UNet Denoiser
However, these methods suffer from high model variance with low performance on high-dimensional datasets due to the ineffective design of the denoiser and are limited in their utilization of ZO techniques.
