New Benchmark for LLM Multi-Turn-Instruct Following!🚀
Can LLMs handle multiple entangled instructions effectively? Our comprehensive Multi-Turn-Instruct dataset evaluates LLMs’ ability to 📜track, 🔄reason on, and ⚖️ resolve conflicts across multiple turns of instructions in
CS PhD student at UIUC, interested in language models and their understanding.
- Thanks, @hengjinlp, for sharing our recent work! In this paper, we investigate how LLMs achieve positional flexibility, such as understanding shuffled sentences and reading long context (a phenomenon also observed in humans). This paper uncovers the hidden computationalYou’re unable to view this Post because this account owner limits who can view their Posts. Learn more
- Welcome to my #AAAI2025 Tutorial, "The Quest for A Science of LMs," today! Time: Feb 26, 2pm-3:45pm Location: Room 113A, Pennsylvania Convention Center Website: glaciohound.github.io/Science-of-LLM… Underline: underline.io/events/487/sch…
- Thank you so much, Heng @hengjinlp! I'm incredibly grateful for your guidance and support throughout this journey and honored to receive the fellowship to continue working on exciting projects. Looking forward to more collaborations with you and Avi Sil @aviaviavi__! 🙌You’re unable to view this Post because this account owner limits who can view their Posts. Learn more
- 🎮 Check out the live demo for LM-Steer “Word Embeddings Are Steers for LMs” (Outstanding Paper ACL 2024) at huggingface.co/spaces/Glacioh…, which can: 1.🕹️Steer model generation 2.🔬Discover word embedding dimensions 3.📊Profile sentences & identify keywords #ACL2024 #LLMs #Science4LM🎖Excited that "LM-Steer: Word Embeddings Are Steers for Language Models" became my another 1st-authored Outstanding Paper #ACL2024 (besides LM-Infinite) We revealed steering roles of word embeddings for continuous, compositional, efficient, interpretable& transferrable control!

