Summary of Do More Details Always Introduce More Hallucinations in Lvlm-based Image Captioning?, by Mingqian Feng et al.
Do More Details Always Introduce More Hallucinations in LVLM-based Image Captioning?by Mingqian Feng, Yunlong Tang,…
Summary of Mitigating Object Hallucinations in Large Vision-language Models with Assembly Of Global and Local Attention, by Wenbin An et al.
Mitigating Object Hallucinations in Large Vision-Language Models with Assembly of Global and Local Attentionby Wenbin…
Summary of Beyond Under-alignment: Atomic Preference Enhanced Factuality Tuning For Large Language Models, by Hongbang Yuan et al.
Beyond Under-Alignment: Atomic Preference Enhanced Factuality Tuning for Large Language Modelsby Hongbang Yuan, Yubo Chen,…
Summary of Post-hoc Utterance Refining Method by Entity Mining For Faithful Knowledge Grounded Conversations, By Yoonna Jang et al.
Post-hoc Utterance Refining Method by Entity Mining for Faithful Knowledge Grounded Conversationsby Yoonna Jang, Suhyune…
Summary of Ask-eda: a Design Assistant Empowered by Llm, Hybrid Rag and Abbreviation De-hallucination, By Luyao Shi et al.
Ask-EDA: A Design Assistant Empowered by LLM, Hybrid RAG and Abbreviation De-hallucinationby Luyao Shi, Michael…
Summary of Confabulation: the Surprising Value Of Large Language Model Hallucinations, by Peiqi Sui et al.
Confabulation: The Surprising Value of Large Language Model Hallucinationsby Peiqi Sui, Eamon Duede, Sophie Wu,…
Summary of Code: Contrasting Self-generated Description to Combat Hallucination in Large Multi-modal Models, by Junho Kim et al.
CODE: Contrasting Self-generated Description to Combat Hallucination in Large Multi-modal Modelsby Junho Kim, Hyunjun Kim,…
Summary of Enhancing Trust in Llms: Algorithms For Comparing and Interpreting Llms, by Nik Bear Brown
Enhancing Trust in LLMs: Algorithms for Comparing and Interpreting LLMsby Nik Bear BrownFirst submitted to…
Summary of Luna: An Evaluation Foundation Model to Catch Language Model Hallucinations with High Accuracy and Low Cost, by Masha Belyi et al.
Luna: An Evaluation Foundation Model to Catch Language Model Hallucinations with High Accuracy and Low…
Summary of Decompose, Enrich, and Extract! Schema-aware Event Extraction Using Llms, by Fatemeh Shiri et al.
Decompose, Enrich, and Extract! Schema-aware Event Extraction using LLMsby Fatemeh Shiri, Van Nguyen, Farhad Moghimifar,…