ICML 2024 "large language models" Papers
180 papers found • Page 1 of 4
$S^2$IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting
Zijie Pan, Yushan Jiang, Sahil Garg et al.
Accelerated Speculative Sampling Based on Tree Monte Carlo
Zhengmian Hu, Heng Huang
Accurate LoRA-Finetuning Quantization of LLMs via Information Retention
Haotong Qin, Xudong Ma, Xingyu Zheng et al.
A Closer Look at the Limitations of Instruction Tuning
Sreyan Ghosh, Chandra Kiran Evuru, Sonal Kumar et al.
Active Preference Learning for Large Language Models
William Muldrew, Peter Hayes, Mingtian Zhang et al.
Adaptive Text Watermark for Large Language Models
Yepeng Liu, Yuheng Bu
Agent Instructs Large Language Models to be General Zero-Shot Reasoners
Nicholas Crispino, Kyle Montgomery, Fankun Zeng et al.
Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models
Bilgehan Sel, Ahmad Al-Tawaha, Vanshaj Khattar et al.
AlphaZero-Like Tree-Search can Guide Large Language Model Decoding and Training
Ziyu Wan, Xidong Feng, Muning Wen et al.
A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?
Agustinus Kristiadi, Felix Strieth-Kalthoff, Marta Skreta et al.
Assessing Large Language Models on Climate Information
Jannis Bulian, Mike Schäfer, Afra Amini et al.
A Tale of Tails: Model Collapse as a Change of Scaling Laws
Elvis Dohmatob, Yunzhen Feng, Pu Yang et al.
Autoformalizing Euclidean Geometry
Logan Murphy, Kaiyu Yang, Jialiang Sun et al.
AutoOS: Make Your OS More Powerful by Exploiting Large Language Models
Huilai Chen, Yuanbo Wen, Limin Cheng et al.
BAT: Learning to Reason about Spatial Sounds with Large Language Models
Zhisheng Zheng, Puyuan Peng, Ziyang Ma et al.
BetterV: Controlled Verilog Generation with Discriminative Guidance
Zehua Pei, Huiling Zhen, Mingxuan Yuan et al.
BiE: Bi-Exponent Block Floating-Point for Large Language Models Quantization
Lancheng Zou, Wenqian Zhao, Shuo Yin et al.
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Wei Huang, Yangdong Liu, Haotong Qin et al.
Can AI Assistants Know What They Don't Know?
Qinyuan Cheng, Tianxiang Sun, Xiangyang Liu et al.
Case-Based or Rule-Based: How Do Transformers Do the Math?
Yi Hu, Xiaojuan Tang, Haotong Yang et al.
Characterizing Truthfulness in Large Language Model Generations with Local Intrinsic Dimension
Fan Yin, Jayanth Srinivasa, Kai-Wei Chang
CHEMREASONER: Heuristic Search over a Large Language Model’s Knowledge Space using Quantum-Chemical Feedback
Henry W. Sprueill, Carl Edwards, Khushbu Agarwal et al.
Coactive Learning for Large Language Models using Implicit User Feedback
Aaron D. Tucker, Kianté Brantley, Adam Cahall et al.
CogBench: a large language model walks into a psychology lab
Julian Coda-Forno, Marcel Binz, Jane Wang et al.
Compressing Large Language Models by Joint Sparsification and Quantization
Jinyang Guo, Jianyu Wu, Zining Wang et al.
ContPhy: Continuum Physical Concept Learning and Reasoning from Videos
Zhicheng Zheng, Xin Yan, Zhenfang Chen et al.
Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation
Haoran Xu, Amr Sharaf, Yunmo Chen et al.
COPAL: Continual Pruning in Large Language Generative Models
Srikanth Malla, Joon Hee Choi, Chiho Choi
Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in low-data regimes
Nabeel Seedat, Nicolas Huynh, Boris van Breugel et al.
Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression
Junyuan Hong, Jinhao Duan, Chenhui Zhang et al.
Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling
Bairu Hou, Yujian Liu, Kaizhi Qian et al.
Deep Fusion: Efficient Network Training via Pre-trained Initializations
Hanna Mazzawi, Xavi Gonzalvo, Michael Wunder et al.
DFA-RAG: Conversational Semantic Router for Large Language Model with Definite Finite Automaton
Yiyou Sun, Junjie Hu, Wei Cheng et al.
Differentially Private Synthetic Data via Foundation Model APIs 2: Text
Chulin Xie, Zinan Lin, Arturs Backurs et al.
DiJiang: Efficient Large Language Models through Compact Kernelization
Hanting Chen, Liuzhicheng Liuzhicheng, Xutao Wang et al.
DiNADO: Norm-Disentangled Neurally-Decomposed Oracles for Controlling Language Models
Sidi Lu, Wenbo Zhao, Chenyang Tao et al.
DistiLLM: Towards Streamlined Distillation for Large Language Models
Jongwoo Ko, Sungnyun Kim, Tianyi Chen et al.
Distinguishing the Knowable from the Unknowable with Language Models
Gustaf Ahdritz, Tian Qin, Nikhil Vyas et al.
DOGE: Domain Reweighting with Generalization Estimation
Simin Fan, Matteo Pagliardini, Martin Jaggi
Do Large Code Models Understand Programming Concepts? Counterfactual Analysis for Code Predicates
Ashish Hooda, Mihai Christodorescu, Miltiadis Allamanis et al.
Do Large Language Models Perform the Way People Expect? Measuring the Human Generalization Function
Keyon Vafa, Ashesh Rambachan, Sendhil Mullainathan
Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explanations
Yanda Chen, Ruiqi Zhong, Narutatsu Ri et al.
DoraemonGPT: Toward Understanding Dynamic Scenes with Large Language Models (Exemplified as A Video Agent)
Zongxin Yang, Guikun Chen, Xiaodi Li et al.
DPZero: Private Fine-Tuning of Language Models without Backpropagation
Liang Zhang, Bingcong Li, Kiran Thekumparampil et al.
DS-Agent: Automated Data Science by Empowering Large Language Models with Case-Based Reasoning
Siyuan Guo, Cheng Deng, Ying Wen et al.
Dual Operating Modes of In-Context Learning
Ziqian Lin, Kangwook Lee
Dynamic Memory Compression: Retrofitting LLMs for Accelerated Inference
Piotr Nawrot, Adrian Łańcucki, Marcin Chochowski et al.
EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty
Yuhui Li, Fangyun Wei, Chao Zhang et al.
eCeLLM: Generalizing Large Language Models for E-commerce from Large-scale, High-quality Instruction Data
Peng, Xinyi Ling, Ziru Chen et al.
EE-LLM: Large-Scale Training and Inference of Early-Exit Large Language Models with 3D Parallelism
Yanxi Chen, Xuchen Pan, Yaliang Li et al.