- Yuan Gong, Hongyin Luo, Alexander H. Liu, Leonid Karlinsky, James R. Glass:
Listen, Think, and Understand. ICLR 2024 - Jian-Feng Cai, Yu Long, Ruixue Wen, Jiaxi Ying:
A Fast and Provable Algorithm for Sparse Phase Retrieval. ICLR 2024 - Chau Pham, Boyi Liu, Yingxiang Yang, Zhengyu Chen, Tianyi Liu, Jianbo Yuan, Bryan A. Plummer, Zhaoran Wang, Hongxia Yang:
Let Models Speak Ciphers: Multiagent Debate through Embeddings. ICLR 2024 - Zhiyuan Liu, Hong Liu, Denny Zhou, Tengyu Ma:
Chain of Thought Empowers Transformers to Solve Inherently Serial Problems. ICLR 2024 - Yichuan Li, Xiyao Ma, Sixing Lu, Kyumin Lee, Xiaohu Liu, Chenlei Guo:
MEND: Meta Demonstration Distillation for Efficient and Effective In-Context Learning. ICLR 2024 - Aditya Bhatt, Daniel Palenicek, Boris Belousov, Max Argus, Artemij Amiranashvili, Thomas Brox, Jan Peters:
CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity. ICLR 2024 - Francisco Vargas, Shreyas Padhy, Denis Blessing, Nikolas Nüsken:
Transport meets Variational Inference: Controlled Monte Carlo Diffusions. ICLR 2024 - Hongyi Wang, Felipe Maia Polo, Yuekai Sun, Souvik Kundu, Eric P. Xing, Mikhail Yurochkin:
Fusing Models with Complementary Expertise. ICLR 2024 - Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, Paul Röttger, Dan Jurafsky, Tatsunori Hashimoto, James Zou:
Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions. ICLR 2024 - Daniel Severo, Lucas Theis, Johannes Ballé:
The Unreasonable Effectiveness of Linear Prediction as a Perceptual Metric. ICLR 2024 - Yifan Jiang, Hao Tang, Jen-Hao Rick Chang, Liangchen Song, Zhangyang Wang, Liangliang Cao:
Efficient-3Dim: Learning a Generalizable Single-image Novel-view Synthesizer in One Day. ICLR 2024 - Tao Dai, Beiliang Wu, Peiyuan Liu, Naiqi Li, Jigang Bao, Yong Jiang, Shu-Tao Xia:
Periodicity Decoupling Framework for Long-term Series Forecasting. ICLR 2024 - Ke Xue, Ren-Jian Wang, Pengyi Li, Dong Li, Jianye Hao, Chao Qian:
Sample-Efficient Quality-Diversity by Cooperative Coevolution. ICLR 2024 - Jen-tse Huang, Wenxuan Wang, Eric John Li, Man Ho Lam, Shujie Ren, Youliang Yuan, Wenxiang Jiao, Zhaopeng Tu, Michael R. Lyu:
On the Humanity of Conversational AI: Evaluating the Psychological Portrayal of LLMs. ICLR 2024 - Shuo He, Chaojie Wang, Guowu Yang, Lei Feng:
Candidate Label Set Pruning: A Data-centric Perspective for Deep Partial-label Learning. ICLR 2024 - Hu Xu, Saining Xie, Xiaoqing Ellen Tan, Po-Yao Huang, Russell Howes, Vasu Sharma, Shang-Wen Li, Gargi Ghosh, Luke Zettlemoyer, Christoph Feichtenhofer:
Demystifying CLIP Data. ICLR 2024 - Jungtaek Kim, Jeongbeen Yoon, Minsu Cho:
Generalized Neural Sorting Networks with Error-Free Differentiable Swap Functions. ICLR 2024 - Mikhail Galkin, Xinyu Yuan, Hesham Mostafa, Jian Tang, Zhaocheng Zhu:
Towards Foundation Models for Knowledge Graph Reasoning. ICLR 2024 - Chen Geng, Hong-Xing Yu, Sida Peng, Xiaowei Zhou, Jiajun Wu:
Neural Polynomial Gabor Fields for Macro Motion Analysis. ICLR 2024 - Haoning Wu, Zicheng Zhang, Erli Zhang, Chaofeng Chen, Liang Liao, Annan Wang, Chunyi Li, Wenxiu Sun, Qiong Yan, Guangtao Zhai, Weisi Lin:
Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Vision. ICLR 2024 - Yijie Lin, Jie Zhang, Zhenyu Huang, Jia Liu, Zujie Wen, Xi Peng:
Multi-granularity Correspondence Learning from Long-term Noisy Videos. ICLR 2024 - Jinyang Jiang, Zeliang Zhang, Chenliang Xu, Zhaofei Yu, Yijie Peng:
One Forward is Enough for Neural Network Training via Likelihood Ratio Method. ICLR 2024 - Wenbo Li, Xin Yu, Kun Zhou, Yibing Song, Zhe Lin:
Image Inpainting via Iteratively Decoupled Probabilistic Modeling. ICLR 2024 - Ziyi Chen, Yi Zhou, Heng Huang:
On the Hardness of Constrained Cooperative Multi-Agent Reinforcement Learning. ICLR 2024 - Xingyao Wang, Zihan Wang, Jiateng Liu, Yangyi Chen, Lifan Yuan, Hao Peng, Heng Ji:
MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback. ICLR 2024 - Junyi Zhu, Zinan Lin, Enshu Liu, Xuefei Ning, Matthew B. Blaschko:
Rescaling Intermediate Features Makes Trained Consistency Models Perform Better. Tiny Papers @ ICLR 2024 - Olivier Laurent, Emanuel Aldea, Gianni Franchi:
A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors. ICLR 2024 - C. Coelho, M. Fernanda P. Costa, Luís L. Ferrás:
Tracing Footprints: Neural Networks Meet Non-integer Order Differential Equations For Modelling Systems with Memory. Tiny Papers @ ICLR 2024 - Zhengyi Luo, Jinkun Cao, Josh Merel, Alexander Winkler, Jing Huang, Kris M. Kitani, Weipeng Xu:
Universal Humanoid Motion Representations for Physics-Based Control. ICLR 2024 - Xiangming Zhu, Huayu Deng, Haochen Yuan, Yunbo Wang, Xiaokang Yang:
Latent Intuitive Physics: Learning to Transfer Hidden Physics from A 3D Video. ICLR 2024