Papers
11,955 papers found
Proving Test Set Contamination in Black-Box Language Models
Yonatan Oren, Nicole Meister, Niladri S. Chatterji et al.
Proximal Policy Gradient Arborescence for Quality Diversity Reinforcement Learning
Sumeet Batra, Bryon Tjanaka, Matthew Christopher Fontaine et al.
Pseudo-Generalized Dynamic View Synthesis from a Video
Xiaoming Zhao, R Alex Colburn, Fangchang Ma et al.
PTaRL: Prototype-based Tabular Representation Learning via Space Calibration
Hangting Ye, Wei Fan, Xiaozhuang Song et al.
PubDef: Defending Against Transfer Attacks From Public Models
Chawin Sitawarin, Jaewon Chang, David Huang et al.
Pushing Boundaries: Mixup's Influence on Neural Collapse
Quinn LeBlanc Fisher, Haoming Meng, Vardan Papyan
Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning
Ted Zadouri, Ahmet Üstün, Arash Ahmadian et al.
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models
Yuhui Xu, Lingxi Xie, Xiaotao Gu et al.
Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Vision
Haoning Wu, Zicheng Zhang, Erli Zhang et al.
QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models
Jing Liu, Ruihao Gong, Xiuying Wei et al.
Quadratic models for understanding catapult dynamics of neural networks
Libin Zhu, Chaoyue Liu, Adityanarayanan Radhakrishnan et al.
Quality-Diversity through AI Feedback
Herbie Bradley, Andrew Dai, Hannah Benita Teufel et al.
Quantifying and Enhancing Multi-modal Robustness with Modality Preference
Zequn Yang, Yake Wei, Ce Liang et al.
Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting
Melanie Sclar, Yejin Choi, Yulia Tsvetkov et al.
Quantifying the Plausibility of Context Reliance in Neural Machine Translation
Gabriele Sarti, Grzegorz Chrupała, Malvina Nissim et al.
Quantifying the Sensitivity of Inverse Reinforcement Learning to Misspecification
Joar Max Viktor Skalse, Alessandro Abate
Quasi-Monte Carlo for 3D Sliced Wasserstein
Khai Nguyen, Nicola Bariletto, Nhat Ho
Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL
Hao Sun, Alihan Hüyük, Mihaela van der Schaar
Querying Easily Flip-flopped Samples for Deep Active Learning
Seong Jin Cho, Gwangsu Kim, Junghyun Lee et al.
Query-Policy Misalignment in Preference-Based Reinforcement Learning
Xiao Hu, Jianxiong Li, Xianyuan Zhan et al.
Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How
Sebastian Pineda Arango, Fabio Ferreira, Arlind Kadra et al.
R.A.C.E.: Robust Adversarial Concept Erasure for Secure Text-to-Image Diffusion Model
Changhoon Kim, Kyle Min, Yezhou Yang
RA-DIT: Retrieval-Augmented Dual Instruction Tuning
Xi Victoria Lin, Xilun Chen, Mingda Chen et al.
Raidar: geneRative AI Detection viA Rewriting
Chengzhi Mao, Carl Vondrick, Hao Wang et al.
RAIN: Your Language Models Can Align Themselves without Finetuning
Yuhui Li, Fangyun Wei, Jinjing Zhao et al.