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📈 Your time-series-paired texts are secretly a time series! 🙌 Real-world time series (stock prices) and texts (financial reports) share similar periodicity and spectrum, unlocking seamless multimodal learning using existing TS models. 🔬 Read more: arxiv.org/abs/2502.08942

🚀 New Paper Alert! 🚀 LLMs struggle with self-correction like O1/R1 because models lack judgment on when to revise vs. when to stay confident. We introduce self-rewarding reasoning LLM, a reasoning framework that: ✅ integrates generator and generative RM into a single LLM. ✅

🔍New findings of knowledge overshadowing! Why do LLMs hallucinate over all true training data? 🤔Can we predict hallucinations even before model training or inference? 🚀Check out our new preprint: [arxiv.org/pdf/2502.16143] The Law of Knowledge Overshadowing: Towards

🔬Graph Self-Supervised Learning Toolkit 🔥We release PyG-SSL, offering a unified framework of 10+ self-supervised choices to pretrain your graph foundation models. 📜Paper: arxiv.org/abs/2412.21151 💻Code: github.com/iDEA-iSAIL-Lab… Have fun!

🚨Call for Papers - 𝗠𝗟𝗼𝗚-𝗚𝗲𝗻𝗔𝗜 @ 𝗞𝗗𝗗 𝟮𝟬𝟮𝟱 Join us at the Workshop on 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗼𝗻 𝗚𝗿𝗮𝗽𝗵𝘀 in the Era of 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 co-located with #KDD2025! 🌐Website: mlgraphworkshop.github.io 🌐Submission Link: openreview.net/group?id=KDD.o…

We'll present 4 papers and 1 keynote talk at #ICLR2025. Prof. Jingrui He and Prof. Hanghang Tong will be at the conference. Let's connect! ☕️

🚨 ICML ’25 SPOTLIGHT 🚨 Taming Knowledge Conflict in Language Models 🤔 Why does your LLM sometimes echo the prompt but other times rely on its “built-in” facts? 🎭 Can we toggle between parametric memory and fresh context without fine-tuning? 🔬 Curious about LLM internals,

Microsoft presents Chain-of-Model Learning for Language Model

🤖 New preprint: We propose ten principles of AI agent economics, offering a framework to understand how AI agents make decisions, influence social interactions, and participate in the broader economy. 📜 Paper: arxiv.org/abs/2505.20273

Today, we introduce our hashtag#CIKM2025 Industry Day Chairs 👏 Jingren Zhou, Soonmin Bae, and Xianfeng Tang are leading this program connecting academia and industry.

Joining the Hundredaire Club💯 as a junior member. A.M. Turing committee please call me anytime.

😲 Not only reasoning?! Inference scaling can now boost LLM safety! 🚀 Introducing Saffron-1: - Reduces attack success rate from 66% to 17.5% - Uses only 59.7 TFLOP compute - Counters latest jailbreak attacks - No model finetuning On the AI2 Refusals benchmark. 📖 Paper:

🧠Let’s teach LLMs to learn smarter, not harder💥[arxiv.org/pdf/2506.06972] 🤖How can LLMs verify complex scientific information efficiently? 🚀We propose modular, reusable atomic reasoning skills that reduce LLMs’ cognitive load to verify scientific claims with little data.

🌠Flow Matching Meets Biology and Life Science: A Survey Flow matching is emerging as a powerful generative paradigm. We comprehensively review its foundations and applications across biology & life science🧬 📚Paper: arxiv.org/abs/2507.17731 💻Resource: github.com/Violet24K/Awes…

Benchmarks don't just measure AI; they define its trajectory. Today, there’s a shortage of truly challenging and useful benchmarks for LLMs — and we believe future forecasting is the next frontier. Introducing TradeBench. trade-bench.live A live-market benchmark where

💥Thrilled to share our new work Reinforce-Ada, which fixes signal collapse in GRPO 🥳No more blind oversampling or dead updates. Just sharper gradients, faster convergence, and stronger models. ⚙️ One-line drop-in. Real gains. arxiv.org/html/2510.0499… github.com/RLHFlow/Reinfo…

With DRAMA being a new paradigm that unifies a wide range of sub-problems, DRAMA-Bot is just the beginning — imagine complex data integration, cleaning, etc, all in one agent. Can’t wait to see what DRAMA unfolds next: DATA SCIENCE IS FULL OF DRAMA🎭🤠