SNUVL

Official account of Vision & Learning lab @SeoulNatlUni for sharing the latest research, news, and more!

[SNUVL @SNUVL]

Compositional Conservatism: A Transductive Approach in Offline Reinforcement Learning., Yeda Song*, Dongwook Lee*, Gunhee Kim

[SNUVL @SNUVL]

Paper accepted to ICLR 2024
@iclr_conf
🎉Super work from our authors! 📷⬇️

[Alfredo Canziani @alfcnz]

Best poster award goes to @soochanl33’s «Recasting Continual Learning as Sequence Modeling» 🥳🥳🥳
Nice graphics, clear explanation, appropriate layout. Plz, more of this! ❤️❤️❤️

[Jaehyeon Son @JaehyeonSon0]

We are presenting our poster now at #1125! @NeurIPSConf #NeurIPS2023

[Hyunwoo Kim @hyunw_kim]

🏆 SODA won the outstanding paper award at #EMNLP2023 ! What an incredible journey that was! I'm grateful for this journey with you @jmhessel @liweijianglw @PeterWestTM @GXiming @YoungjaeYu3 @peizNLP @Ronan_LeBras @malihealikhani @gunheekim @MaartenSap @YejinChoinka & @allen_ai💙

[Soochan Lee @SoochanL33]

Is a sequence model all you need for continual learning? Our NeurIPS 2023 paper "Recasting Continual Learning as Sequence Modeling" points out that continual learning is inherently a sequence modeling problem, and sequence models can be employed as CL solutions. (1/5)

[Hyunwoo Kim @hyunw_kim]

🤔Do you think GPT-4 has Theory of Mind? We give you FANToM👻, a new benchmark for stress-testing machine ToM in interactions while teasing out shallow heuristic cues. LLMs are not even close to having ToM. They all score near0️⃣, whereas humans score 90!
🧵https://t.co/5LqnsKQTCX

[SNUVL @SNUVL]

@NeurIPSConf Recasting Continual Learning as Sequence Modeling Soochan Lee, Jaehyeon Son, Gunhee Kim

[SNUVL @SNUVL]

2 papers accepted to NeurIPS 2023
@NeurIPSConf
🎉Super works from our authors! 📷⬇️

[SNUVL @SNUVL]

@emnlpmeeting FANToM: A Benchmark for Analyzing Theory of Mind in Conversations, Hyunwoo Kim, Melanie Sclar, Xuhui Zhou, Ronan Le Bras, Gunhee Kim, Yejin Choi, Maarten Sap

[SNUVL @SNUVL]

4 papers accepted to EMNLP 2023
@emnlpmeeting
🎉Super works from our authors! 📷⬇️

[SNUVL @SNUVL]

@emnlpmeeting SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization, Hyunwoo Kim, Jack Hessel, Liwei Jiang, Peter West, Ximing Lu, Youngjae Yu, Pei Zhou, Ronan Le Bras, Malihe Alikhani, Gunhee Kim, Maarten Sap, Yejin Choi

[SNUVL @SNUVL]

@emnlpmeeting Can Language Models Laugh at YouTube Short-form Videos?, Dayoon Ko, Sangho Lee, Gunhee Kim

[SNUVL @SNUVL]

@emnlpmeeting mRedditSum: A Multimodal Abstractive Summarization Dataset of Reddit Threads with Images, Keighley Overbay, Jaewoo Ahn, Fatemeh Pesaran zadeh, Joonsuk Park, Gunhee Kim

[SNUVL @SNUVL]

@NeurIPSConf Federated Learning via Meta-Variational Dropout
Insu Jeon, Minui Hong, Junhyeog Yun, Gunhee Kim

[SNUVL @SNUVL]

Recursion of Thought: A Divide-and-Conquer Approach to Multi-Context Reasoning with Language Models (Short, Findings)
Soochan Lee and Gunhee Kim

[SNUVL @SNUVL]

3 papers accepted to ACL 2023 @aclmeeting
🎉Super works from our authors! 🤩⬇️

[SNUVL @SNUVL]

- SQuARe: A Large-Scale Dataset of Sensitive Questions and Acceptable Responses Created through Human-Machine Collaboration
H. Lee, S. Hong, J. Park, T. Kim, M. Cha, Y. Choi, B. Kim, G. Kim, E. Lee, Y. Lim, A. Oh, S. Park and J. Ha

[SNUVL @SNUVL]

- MPCHAT: Towards Multimodal Persona-Grounded Conversation
Jaewoo Ahn, Yeda Song, Sangdoo Yun and Gunhee Kim

[clem 🤗 @ClementDelangue]

Cool new dialog dataset from @allen_ai! https://t.co/knquBGnvAW