Han Wang
@hwang98.bsky.social
PhD student @unc @unccs @uncnlp; Formerly Intern @AmazonScience @MSFTResearch @NlpWestlake. RT & like ≠ endorsements. Views are my own. He/him
hannight.github.io
hannight.github.io
Reposted by Han Wang
🚨Real-world retrieval is messy: queries are ambiguous or docs conflict & have incorrect/irrelevant info. How can we jointly address these problems?
➡️RAMDocs: challenging dataset w/ ambiguity, misinformation & noise
➡️MADAM-RAG: multi-agent framework, debates & aggregates evidence across sources
🧵⬇️
➡️RAMDocs: challenging dataset w/ ambiguity, misinformation & noise
➡️MADAM-RAG: multi-agent framework, debates & aggregates evidence across sources
🧵⬇️
April 18, 2025 at 5:06 PM
🚨Real-world retrieval is messy: queries are ambiguous or docs conflict & have incorrect/irrelevant info. How can we jointly address these problems?
➡️RAMDocs: challenging dataset w/ ambiguity, misinformation & noise
➡️MADAM-RAG: multi-agent framework, debates & aggregates evidence across sources
🧵⬇️
➡️RAMDocs: challenging dataset w/ ambiguity, misinformation & noise
➡️MADAM-RAG: multi-agent framework, debates & aggregates evidence across sources
🧵⬇️
Reposted by Han Wang
🎉 Congrats to the awesome students, postdocs, & collaborators for this exciting batch of #ICLR2025 and #NAACL2025 accepted papers (FYI some are on the academic/industry job market and a great catch 🙂), on diverse, important topics such as:
-- adaptive data generation environments/policies
...
🧵
-- adaptive data generation environments/policies
...
🧵
January 27, 2025 at 9:38 PM
🎉 Congrats to the awesome students, postdocs, & collaborators for this exciting batch of #ICLR2025 and #NAACL2025 accepted papers (FYI some are on the academic/industry job market and a great catch 🙂), on diverse, important topics such as:
-- adaptive data generation environments/policies
...
🧵
-- adaptive data generation environments/policies
...
🧵
Reposted by Han Wang
Deeply honored & humbled to have received the Presidential #PECASE Award by the @WhiteHouse and @POTUS office! 🙏
Most importantly, very grateful to my amazing mentors, students, postdocs, collaborators, and friends+family for making this possible, and for making the journey worthwhile + beautiful 💙
Most importantly, very grateful to my amazing mentors, students, postdocs, collaborators, and friends+family for making this possible, and for making the journey worthwhile + beautiful 💙
🎉 Congratulations to Prof. @mohitbansal.bsky.social for receiving the Presidential #PECASE Award by @WhiteHouse, which is the highest honor bestowed by US govt. on outstanding scientists/engineers who show exceptional potential for leadership early in their careers!
whitehouse.gov/ostp/news-up...
whitehouse.gov/ostp/news-up...
January 15, 2025 at 4:45 PM
Deeply honored & humbled to have received the Presidential #PECASE Award by the @WhiteHouse and @POTUS office! 🙏
Most importantly, very grateful to my amazing mentors, students, postdocs, collaborators, and friends+family for making this possible, and for making the journey worthwhile + beautiful 💙
Most importantly, very grateful to my amazing mentors, students, postdocs, collaborators, and friends+family for making this possible, and for making the journey worthwhile + beautiful 💙
Reposted by Han Wang
🚨 I’m on the academic job market!
j-min.io
I work on ✨Multimodal AI✨, advancing reasoning in understanding & generation by:
1⃣ Making it scalable
2⃣ Making it faithful
3⃣ Evaluating + refining it
Completing my PhD at UNC (w/ @mohitbansal.bsky.social).
Happy to connect (will be at #NeurIPS2024)!
👇🧵
j-min.io
I work on ✨Multimodal AI✨, advancing reasoning in understanding & generation by:
1⃣ Making it scalable
2⃣ Making it faithful
3⃣ Evaluating + refining it
Completing my PhD at UNC (w/ @mohitbansal.bsky.social).
Happy to connect (will be at #NeurIPS2024)!
👇🧵
December 7, 2024 at 10:32 PM
🚨 I’m on the academic job market!
j-min.io
I work on ✨Multimodal AI✨, advancing reasoning in understanding & generation by:
1⃣ Making it scalable
2⃣ Making it faithful
3⃣ Evaluating + refining it
Completing my PhD at UNC (w/ @mohitbansal.bsky.social).
Happy to connect (will be at #NeurIPS2024)!
👇🧵
j-min.io
I work on ✨Multimodal AI✨, advancing reasoning in understanding & generation by:
1⃣ Making it scalable
2⃣ Making it faithful
3⃣ Evaluating + refining it
Completing my PhD at UNC (w/ @mohitbansal.bsky.social).
Happy to connect (will be at #NeurIPS2024)!
👇🧵
Elias is a brilliant and supportive researcher and mentor, and I am enjoying collaborating with him. I can't wait to see what he will achieve as a professor!
🚨 I am on the faculty job market this year 🚨
I will be presenting at #NeurIPS2024 and am happy to chat in-person or digitally!
I work on developing AI agents that can collaborate and communicate robustly with us and each other.
More at: esteng.github.io and in thread below
🧵👇
I will be presenting at #NeurIPS2024 and am happy to chat in-person or digitally!
I work on developing AI agents that can collaborate and communicate robustly with us and each other.
More at: esteng.github.io and in thread below
🧵👇
December 6, 2024 at 2:36 AM
Elias is a brilliant and supportive researcher and mentor, and I am enjoying collaborating with him. I can't wait to see what he will achieve as a professor!
Reposted by Han Wang
🚨 Reverse Thinking Makes LLMs Stronger Reasoners
We can often reason from a problem to a solution and also in reverse to enhance our overall reasoning. RevThink shows that LLMs can also benefit from reverse thinking 👉 13.53% gains + sample efficiency + strong generalization (on 4 OOD datasets)!
We can often reason from a problem to a solution and also in reverse to enhance our overall reasoning. RevThink shows that LLMs can also benefit from reverse thinking 👉 13.53% gains + sample efficiency + strong generalization (on 4 OOD datasets)!
December 2, 2024 at 7:29 PM
🚨 Reverse Thinking Makes LLMs Stronger Reasoners
We can often reason from a problem to a solution and also in reverse to enhance our overall reasoning. RevThink shows that LLMs can also benefit from reverse thinking 👉 13.53% gains + sample efficiency + strong generalization (on 4 OOD datasets)!
We can often reason from a problem to a solution and also in reverse to enhance our overall reasoning. RevThink shows that LLMs can also benefit from reverse thinking 👉 13.53% gains + sample efficiency + strong generalization (on 4 OOD datasets)!