sayzardfly51fly (@fly51fly)
Stanford 연구진이 긴 문서 집합에서 질문응답을 더 확장 가능하게 수행하기 위한 구조화된 추론 방법인 ‘Contexts are Never Long Enough’를 제안했습니다. 긴 컨텍스트의 한계를 줄이고, 여러 문서를 활용한 QA 성능 향상을 목표로 하는 연구입니다.
UKP Lab👥 Justus-Jonas Erker (UKP Lab/Technische Universität Darmstadt), Nils Reimers (Cohere), Iryna Gurevych (UKP Lab/Technische Universität Darmstadt)
See you at Hashtag#EACL2026 in Rabat 🕌!
#UKPLab #NLP #NLProc #InformationRetrieval #DenseRetrieval #MultiHop #FactChecking #QuestionAnswering #RAG
NFDI4DSCall for participation: *SciVQA* Shared Task (https://sdproc.org/2025/scivqa.html)
@NFDI4DS members Ekaterina Borisova and Georg Rehm are organizing a shared task “Scientific Visual Question Answering Shared Task (SciVQA)” on July 31 or August 1st, 2025 in Vienna, Austria, hosted as part of the SDP 2025 Workshop.
Deadline for system submissions: May 16, 2025
#chart
#diagram
#multimodalQA
#visualattributes
#questionanswering
#arXiv
#SciVQA
#SDP2025
#ACL2025
#Vienna
#codabench
#huggingface
#NFDI4DS
Auriol DegbeloOur Institute is hiring. If you are interested in working at the intersection of conversational question-answering and geographic knowledge graphs, we would love to hear from you!
#knowledgegraph #questionanswering
Full job ad: https://www.verw.tu-dresden.de/StellAus/stelle.asp?id=11872&lang=de&style=verw
PyLadies Bot📝 "PDF-Based Question Answering with Amazon Bedrock and Haystack"
👤 Bilge Yucel (@bilgeyucel)
#pyladies #python #amazonwebservices #haystack #amazonbedrock #questionanswering #opensearch
michabbb#TechNews: #Qwen Releases New #VisionLanguage #LLM Qwen2-VL 🖥️👁️
After a year of development, #Qwen has released Qwen2-VL, its latest #AI system for interpreting visual and textual information. 🚀
Key Features of Qwen2-VL:
1. 🖼️ Image Understanding:
Qwen2-VL shows performance on #VisualUnderstanding benchmarks including #MathVista, #DocVQA, #RealWorldQA, and #MTVQA.
2. 🎬 Video Analysis:
Qwen2-VL can analyze videos over 20 minutes in length. This is achieved through online streaming capabilities, allowing for video-based #QuestionAnswering, #Dialog, and #ContentCreation. #VideoAnalysis
3. 🤖 Device Integration:
The #AI can be integrated with #mobile phones, #robots, and other devices. It uses reasoning and decision-making abilities to interpret visual environments and text instructions for device control. #AIAssistants 📱
4. 🌍 Multilingual Capabilities:
Qwen2-VL understands text in images across multiple languages. It supports most European languages, Japanese, Korean, Arabic, Vietnamese, among others, in addition to English and Chinese. #MultilingualAI
This release represents an advancement in #ArtificialIntelligence, combining visual perception and language understanding. 🧠 Potential applications include #education, #healthcare, #robotics, and #contentmoderation.
IDHNMBZUAI is looking to recruit postdoctoral researchers (https://mbzuai.ac.ae/) to work on #Arabic #NLP. The ideal candidate should be particularly interested in #Dialectal Arabic, Arabic #LLMs, #QuestionAnswering, but candidates with experience on Arabic NLP in general will also be considered.
To apply, please write directly to Preslav Nakov:
[email protected]
To apply, please write directly to Preslav Nakov:
[email protected]
Tech ChilliMeet GraphRAG: Microsoft’s New Graph-Based AI Method for Superior Data Insights.
#GraphRAG #Microsoft #AI #DataInsights #TechInnovation #GitHub #DataRetrieval #AItechnology #QuestionAnswering #DataAnalysis #FutureOfAI #GraphBasedAI #TechTrends #Innovation
Meet GraphRAG: Microsoft’s New Graph-Based AI Method for Superior Data Insights
Microsoft introduces GraphRAG, a graph-based AI method for retrieval-augmented generation, now available on GitHub. This tool enhances data retrieval and question answering for private or unseen datasets, offering a systematic and complete response production.
Jens Lehmann🎉 We developed a prompting method for improved (and more human-like) LLM reasoning and applied it to hybrid question answering, surpassing the GPT-4 baseline. 🚀
Thanks to my co-authors Dhananjay, Preetam and @SaharVahdati ! We'll present the work at #ACL2024 in Bangkok this year where I hope I'll be able to meet a few of you.
Blog post: https://linkedin.com/pulse/beyond-boundaries-human-like-approach-question-over-sources-lehmann-dhtne
Beyond Boundaries: A Human-like Approach for Question Answering over Structured and Unstructured Information Sources
Together with my co-authors, we are excited to share our work on an easy-to-apply method to improve LLM reasoning and how we applied it for question answering across heterogenous sources. 🚀 Language models relying solely on their internal parameters lack knowledge about recent knowledge as well as
Dave in 🏴Very biased, but also very excited about Khyathi Chandu's presentation of our new proposed shared task at #INLG2023: "LowReCorp: The Low-Resource NLG Corpus Building Challenge"
Join the #SharedTask during the coming year if you want to use our UI or task design to collect #NLG data for #LowResourceLanguages!
#DialogueSummarization #QuestionAnswering #ResponseGeneration
