Megagon Labs (@megagonlabs) 's Twitter Profile
Megagon Labs

@megagonlabs

Megagon Labs advances state-of-the-art research in AI and builds technologies that impact the world through online services. #NLP #AI #ML #NLP4HR #LLM #RAG

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linkhttp://www.megagon.ai calendar_today04-06-2018 22:46:13

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🧠#LLM agents often fail in ways that are hard to interpret. Our new #VeriLA framework helps humans systematically verify and understand these failures. Catch the presentation by Yoo Yeon Sung@NAACL2025 at the HEAL Workshop at #CHI2025 on April 26th! 📰 megagon.ai/publications/v… #AgenticAI

🧠#LLM agents often fail in ways that are hard to interpret. Our new #VeriLA framework helps humans systematically verify and understand these failures.

Catch the presentation by <a href="/YooYeonSung1/">Yoo Yeon Sung@NAACL2025</a> at the HEAL Workshop at #CHI2025 on April 26th!

📰 megagon.ai/publications/v…
#AgenticAI
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Attending hashtag#NAACL25? Come find us at Booth #1. Get more info megagon.ai/links/ #LLM #AI #agents #CompoundAI #NLP #HR #HCI #Data #benchmarks #matching #summarization

Attending hashtag#NAACL25? Come find us at Booth #1. Get more info megagon.ai/links/

#LLM #AI #agents #CompoundAI #NLP #HR #HCI #Data #benchmarks #matching #summarization
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📣Hayate Iso will present at #NAACL25. Join the discussion at 10:30 a.m. GMT in Hall 3 Poster 4. Read the paper: megagon.ai/publications/e… #fairness #LLM #AI #HR

📣<a href="/iso_map/">Hayate Iso</a> will present at #NAACL25. Join the discussion at 10:30 a.m. GMT in Hall 3 Poster 4. 
Read the paper: megagon.ai/publications/e…

#fairness #LLM #AI #HR
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#NAACL25 come join Pouya Pezeshkpour for his poster presentation on "LLMs Are Not Intelligent Thinkers: Introducing Mathematical Topic Tree Benchmark for Comprehensive Evaluation of LLMs." arxiv.org/abs/2406.05194

#NAACL25 come join <a href="/PPezeshkpour/">Pouya Pezeshkpour</a> for his poster presentation on "LLMs Are Not Intelligent Thinkers: Introducing Mathematical Topic Tree Benchmark for Comprehensive Evaluation of LLMs." arxiv.org/abs/2406.05194
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How well do language models cope with complexity beyond a single document? As real-world AI applications grow more complex, robust multi-document reasoning becomes critical, and current LLMs are showing signs of strain. In this article, we explore three of our recent research

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If you're interested in how LLMs handle the' messy, ambiguous nature of multi-document inputs and where they fall short, this is for you. #NAACL2025 #ICLR2025 #LLMs #MultiDocument #Summarization #Reasoning #NLPResearch #MegagonLabs #AI #MachineLearning #NLP Pouya Pezeshkpour Seiji Maekawa

If you're interested in how LLMs handle the' messy, ambiguous nature of multi-document inputs and where they fall short, this is for you.

#NAACL2025 #ICLR2025 #LLMs #MultiDocument #Summarization #Reasoning #NLPResearch #MegagonLabs #AI #MachineLearning #NLP <a href="/PPezeshkpour/">Pouya Pezeshkpour</a> <a href="/SAYg_7/">Seiji Maekawa</a>
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How can enterprises adopt agentic AI without reinventing their entire tech stack? megagon.ai/blue-designing… In Volume 2 of the Blue article series, we take a deeper look at what it takes to make existing data, models, and services work in agentic workflows and what “agentic for

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📢 Find us at #MLSys2025 this week! 📣 Eser Kandogan 🇺🇦 will be presenting at the sponsor talk about #Blue, our open-source agentic compound #AI framework for enterprises 👋 Our team is at our exhibitor booth giving away goodies, ready to talk about job and internship

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🚀 𝗥𝗲𝘁𝗵𝗶𝗻𝗸𝗶𝗻𝗴 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗳𝗼𝗿 𝘁𝗵𝗲 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗘𝗿𝗮 In our latest blog post, megagon.ai/blue-designing…, we dive into how Megagon Labs' 𝗕𝗹𝘂𝗲 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 reimagines enterprise architectures to support intelligent,

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🔍 𝗖𝗮𝗻 𝘁𝗼𝗱𝗮𝘆’𝘀 𝗟𝗟𝗠𝘀 𝗮𝗰𝗰𝘂𝗿𝗮𝘁𝗲𝗹𝘆 𝗾𝘂𝗲𝗿𝘆 𝗿𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗴𝗿𝗮𝗽𝗵𝘀? 𝗗𝗲𝘀𝗽𝗶𝘁𝗲 𝘁𝗵𝗲𝗶𝗿 𝗴𝗿𝗼𝘄𝗶𝗻𝗴 𝗰𝗮𝗽𝗮𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀, 𝗹𝗮𝗿𝗴𝗲 𝗹𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗺𝗼𝗱𝗲𝗹𝘀 𝘀𝘁𝗶𝗹𝗹 𝘀𝘁𝗿𝘂𝗴𝗴𝗹𝗲 𝘄𝗶𝘁𝗵 𝗽𝗿𝗲𝗰𝗶𝘀𝗲,

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🚨 We are excited to announce that our paper, "FactLens: Benchmarking Fine-Grained Fact Verification", has been accepted at #ACL2025 Findings! megagon.ai/publications/f… 🔍 As #LLMs become increasingly prevalent, ensuring the factual accuracy of their outputs is paramount.