"natural language processing" Papers
22 papers found
Conference
AdaptDel: Adaptable Deletion Rate Randomized Smoothing for Certified Robustness
Zhuoqun Huang, Neil Marchant, Olga Ohrimenko et al.
AdaptMI: Adaptive Skill-based In-context Math Instructions for Small Language Models
Yinghui He, Abhishek Panigrahi, Yong Lin et al.
Belief-Calibrated Multi-Agent Consensus Seeking for Complex NLP Tasks
Wentao Deng, Jiahuan Pei, Zhiwei Xu et al.
Causal Reasoning and Large Language Models: Opening a New Frontier for Causality
Chenhao Tan, Robert Ness, Amit Sharma et al.
Enhancing Transformers Through Conditioned Embedded Tokens
Hemanth Saratchandran, Simon Lucey
FormalAlign: Automated Alignment Evaluation for Autoformalization
Jianqiao Lu, Yingjia Wan, Yinya Huang et al.
LongProc: Benchmarking Long-Context Language Models on Long Procedural Generation
Xi Ye, Fangcong Yin, Yinghui He et al.
MURKA: Multi-Reward Reinforcement Learning with Knowledge Alignment for Optimization Tasks
WANTONG XIE, Yi-Xiang Hu, Jieyang Xu et al.
Overcoming Long Context Limitations of State Space Models via Context Dependent Sparse Attention
Zhihao Zhan, Jianan Zhao, Zhaocheng Zhu et al.
Till the Layers Collapse: Compressing a Deep Neural Network Through the Lenses of Batch Normalization Layers.
Zhu Liao, Nour Hezbri, Victor Quétu et al.
Torch-Uncertainty: Deep Learning Uncertainty Quantification
Adrien Lafage, Olivier Laurent, Firas Gabetni et al.
Zero-Shot Performance Prediction for Probabilistic Scaling Laws
Viktoria Schram, Markus Hiller, Daniel Beck et al.
Breaking through the learning plateaus of in-context learning in Transformer
Jingwen Fu, Tao Yang, Yuwang Wang et al.
Conformal Autoregressive Generation: Beam Search with Coverage Guarantees
Nicolas Deutschmann, Marvin Alberts, María Rodríguez Martínez
CurBench: Curriculum Learning Benchmark
Yuwei Zhou, Zirui Pan, Xin Wang et al.
Defense against Backdoor Attack on Pre-trained Language Models via Head Pruning and Attention Normalization
Xingyi Zhao, Depeng Xu, Shuhan Yuan
Dialogue for Prompting: A Policy-Gradient-Based Discrete Prompt Generation for Few-Shot Learning
Chengzhengxu Li, Xiaoming Liu, Yichen Wang et al.
Few-Shot Character Understanding in Movies as an Assessment to Meta-Learning of Theory-of-Mind
Mo Yu, Qiujing Wang, Shunchi Zhang et al.
OptiMUS: Scalable Optimization Modeling with (MI)LP Solvers and Large Language Models
Ali AhmadiTeshnizi, Wenzhi Gao, Madeleine Udell
Removing Spurious Concepts from Neural Network Representations via Joint Subspace Estimation
Floris Holstege, Bram Wouters, Noud van Giersbergen et al.
Revisiting Character-level Adversarial Attacks for Language Models
Elias Abad Rocamora, Yongtao Wu, Fanghui Liu et al.
SpikeZIP-TF: Conversion is All You Need for Transformer-based SNN
kang you, Zekai Xu, Chen Nie et al.