:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Agarwal, Mayank, Shen, Yikang, Wang, Bailin, Kim, Yoon, Chen, Jie
Format:	Preprint
Published:	2024
Subjects:	Computation and Language
Online Access:	https://arxiv.org/abs/2401.10716
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Gated Linear Attention Transformers with Hardware-Efficient Training
by: Yang, Songlin, et al.
Published: (2023)

Parallelizing Linear Transformers with the Delta Rule over Sequence Length
by: Yang, Songlin, et al.
Published: (2024)

FlashFormer: Whole-Model Kernels for Efficient Low-Batch Inference
by: Nrusimha, Aniruddha, et al.
Published: (2025)

Learning to Decode Collaboratively with Multiple Language Models
by: Shen, Shannon Zejiang, et al.
Published: (2024)

In-Context Language Learning: Architectures and Algorithms
by: Akyürek, Ekin, et al.
Published: (2024)

Exploring Data-Efficient Adaptation of Large Language Models for Code Generation
by: Jiang, Xue, et al.
Published: (2024)

CodeMirage: Hallucinations in Code Generated by Large Language Models
by: Agarwal, Vibhor, et al.
Published: (2024)

PaTH Attention: Position Encoding via Accumulating Householder Transformations
by: Yang, Songlin, et al.
Published: (2025)

A Survey on Large Language Models for Code Generation
by: Jiang, Juyong, et al.
Published: (2024)

Lemur: Harmonizing Natural Language and Code for Language Agents
by: Xu, Yiheng, et al.
Published: (2023)

Octo-planner: On-device Language Model for Planner-Action Agents
by: Chen, Wei, et al.
Published: (2024)

Reasoning or Reciting? Exploring the Capabilities and Limitations of Language Models Through Counterfactual Tasks
by: Wu, Zhaofeng, et al.
Published: (2023)

Efficient Continual Pre-training by Mitigating the Stability Gap
by: Guo, Yiduo, et al.
Published: (2024)

Defining and Evaluating Decision and Composite Risk in Language Models Applied to Natural Language Inference
by: Shen, Ke, et al.
Published: (2024)

Granite Code Models: A Family of Open Foundation Models for Code Intelligence
by: Mishra, Mayank, et al.
Published: (2024)

Dense Training, Sparse Inference: Rethinking Training of Mixture-of-Experts Language Models
by: Pan, Bowen, et al.
Published: (2024)

Toward Reliable Clinical Coding with Language Models: Verification and Lightweight Adaptation
by: Yuan, Zhangdie, et al.
Published: (2025)

Beyond Monolingual Assumptions: A Survey of Code-Switched NLP in the Era of Large Language Models across Modalities
by: Sheth, Rajvee, et al.
Published: (2025)

Mitigating the Impact of Outlier Channels for Language Model Quantization with Activation Regularization
by: Nrusimha, Aniruddha, et al.
Published: (2024)

Implicit Representations of Grammaticality in Language Models
by: Wang, Yingshan Susan, et al.
Published: (2026)

LongCodeZip: Compress Long Context for Code Language Models
by: Shi, Yuling, et al.
Published: (2025)

Enhancing Multilingual Language Models for Code-Switched Input Data
by: Xie, Katherine, et al.
Published: (2025)

CodeMind: Evaluating Large Language Models for Code Reasoning
by: Liu, Changshu, et al.
Published: (2024)

PaT: Planning-after-Trial for Efficient Test-Time Code Generation
by: Yoon, Youngsik, et al.
Published: (2026)

Learning to Reduce: Optimal Representations of Structured Data in Prompting Large Language Models
by: Lee, Younghun, et al.
Published: (2024)

Evaluating Language Models for Efficient Code Generation
by: Liu, Jiawei, et al.
Published: (2024)

GraphLAMA: Enabling Efficient Adaptation of Graph Language Models with Limited Annotations
by: Chen, Junze, et al.
Published: (2025)

PythonSaga: Redefining the Benchmark to Evaluate Code Generating LLMs
by: Yadav, Ankit, et al.
Published: (2024)

NL-Debugging: Exploiting Natural Language as an Intermediate Representation for Code Debugging
by: Zhang, Weiming, et al.
Published: (2025)

Parallel-SFT: Improving Zero-Shot Cross-Programming-Language Transfer for Code RL
by: Wu, Zhaofeng, et al.
Published: (2026)

CodeSimpleQA: Scaling Factuality in Code Large Language Models
by: Yang, Jian, et al.
Published: (2025)

Code Comparison Tuning for Code Large Language Models
by: Jiang, Yufan, et al.
Published: (2024)

Diversity Measurement and Subset Selection for Instruction Tuning Datasets
by: Wang, Peiqi, et al.
Published: (2024)

Scaling Granite Code Models to 128K Context
by: Stallone, Matt, et al.
Published: (2024)

IRCoder: Intermediate Representations Make Language Models Robust Multilingual Code Generators
by: Paul, Indraneil, et al.
Published: (2024)

Weber's Law in Transformer Magnitude Representations: Efficient Coding, Representational Geometry, and Psychophysical Laws in Language Models
by: Cacioli, Jon-Paul
Published: (2026)

An Evaluation of Estimative Uncertainty in Large Language Models
by: Tang, Zhisheng, et al.
Published: (2024)

Improving Natural Language Capability of Code Large Language Model
by: Li, Wei, et al.
Published: (2024)

DA-Code: Agent Data Science Code Generation Benchmark for Large Language Models
by: Huang, Yiming, et al.
Published: (2024)

CodeComp: Structural KV Cache Compression for Agentic Coding
by: Chen, Qiujiang, et al.
Published: (2026)