:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhang, Bohan, Wang, Yixin, Dhillon, Paramveer S.
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Artificial Intelligence Machine Learning
Online Access:	https://arxiv.org/abs/2404.00207
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Policy Learning with a Natural Language Action Space: A Causal Approach
by: Zhang, Bohan, et al.
Published: (2025)

Can Good Writing Be Generative? Expert-Level AI Writing Emerges through Fine-Tuning on High-Quality Books
by: Chakrabarty, Tuhin, et al.
Published: (2026)

Readers Prefer Outputs of AI Trained on Copyrighted Books over Expert Human Writers
by: Chakrabarty, Tuhin, et al.
Published: (2025)

Who Owns the Text? Design Patterns for Preserving Authorship in AI-Assisted Writing
by: Zhang, Bohan, et al.
Published: (2026)

L3Ms -- Lagrange Large Language Models
by: Dhillon, Guneet S., et al.
Published: (2024)

Causality for Large Language Models
by: Wu, Anpeng, et al.
Published: (2024)

CITER: Collaborative Inference for Efficient Large Language Model Decoding with Token-Level Routing
by: Zheng, Wenhao, et al.
Published: (2025)

Causal Evaluation of Language Models
by: Chen, Sirui, et al.
Published: (2024)

Collaborative Performance Prediction for Large Language Models
by: Zhang, Qiyuan, et al.
Published: (2024)

Non-Markovian Discrete Diffusion with Causal Language Models
by: Zhang, Yangtian, et al.
Published: (2025)

LLM4Causal: Democratized Causal Tools for Everyone via Large Language Model
by: Jiang, Haitao, et al.
Published: (2023)

ME-Switch: A Memory-Efficient Expert Switching Framework for Large Language Models
by: Liu, Jing, et al.
Published: (2024)

Beware of Calibration Data for Pruning Large Language Models
by: Ji, Yixin, et al.
Published: (2024)

Collaborative Causal Sensemaking: Closing the Complementarity Gap in Human-AI Decision Support
by: Jain, Raunak
Published: (2025)

Mitigating Hallucinations in Large Language Models via Causal Reasoning
by: Li, Yuangang, et al.
Published: (2025)

CausalVLBench: Benchmarking Visual Causal Reasoning in Large Vision-Language Models
by: Komanduri, Aneesh, et al.
Published: (2025)

QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models
by: Liu, Jing, et al.
Published: (2023)

Prompting Fairness: Integrating Causality to Debias Large Language Models
by: Li, Jingling, et al.
Published: (2024)

Dual Debiasing for Noisy In-Context Learning for Text Generation
by: Liang, Siqi, et al.
Published: (2025)

Compositional Causal Reasoning Evaluation in Language Models
by: Maasch, Jacqueline R. M. A., et al.
Published: (2025)

CLadder: Assessing Causal Reasoning in Language Models
by: Jin, Zhijing, et al.
Published: (2023)

MiniCache: KV Cache Compression in Depth Dimension for Large Language Models
by: Liu, Akide, et al.
Published: (2024)

Calibrating Long-form Generations from Large Language Models
by: Huang, Yukun, et al.
Published: (2024)

Are the Values of LLMs Structurally Aligned with Humans? A Causal Perspective
by: Kang, Yipeng, et al.
Published: (2024)

Scaling Inference-Efficient Language Models
by: Bian, Song, et al.
Published: (2025)

Discovering Hierarchical Latent Capabilities of Language Models via Causal Representation Learning
by: Jin, Jikai, et al.
Published: (2025)

Large Language Models for Human-Machine Collaborative Particle Accelerator Tuning through Natural Language
by: Kaiser, Jan, et al.
Published: (2024)

TabDLM: Free-Form Tabular Data Generation via Joint Numerical-Language Diffusion
by: Cai, Donghong, et al.
Published: (2026)

Task-Stratified Knowledge Scaling Laws for Post-Training Quantized Large Language Models
by: Zhou, Chenxi, et al.
Published: (2025)

A Framework for Inference Inspired by Human Memory Mechanisms
by: Zeng, Xiangyu, et al.
Published: (2023)

Syntactic Control of Language Models by Posterior Inference
by: Xefteri, Vicky, et al.
Published: (2025)

Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees
by: Chen, Sijia, et al.
Published: (2024)

When Less is Enough: Efficient Inference via Collaborative Reasoning
by: Chen, Yilei, et al.
Published: (2026)

A Toolbox, Not a Hammer -- Multi-TAG: Scaling Math Reasoning with Multi-Tool Aggregation
by: Yao, Bohan, et al.
Published: (2025)

Are UFOs Driving Innovation? The Illusion of Causality in Large Language Models
by: Carro, María Victoria, et al.
Published: (2024)

Do Large Language Models Show Biases in Causal Learning?
by: Carro, Maria Victoria, et al.
Published: (2024)

Model Compression and Efficient Inference for Large Language Models: A Survey
by: Wang, Wenxiao, et al.
Published: (2024)

A Meta-Learning Perspective on Transformers for Causal Language Modeling
by: Wu, Xinbo, et al.
Published: (2023)

Unveiling Causal Reasoning in Large Language Models: Reality or Mirage?
by: Chi, Haoang, et al.
Published: (2025)

FlattenQuant: Breaking Through the Inference Compute-bound for Large Language Models with Per-tensor Quantization
by: Zhang, Yi, et al.
Published: (2024)