Lita: Light Agent Uncovers the Agentic Coding Capabilities of LLMs
Fuente:
arXiv
Saved in:
| Main Authors: | Dai, Hankun, Wang, Maoquan, Qi, Mengnan, Zhang, Yikai, Jin, Zijian, Yao, Yongqiang, Huang, Yufan, Fu, Shengyu, Nallipogu, Elsie |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Sphinx: Benchmarking and Modeling for LLM-Driven Pull Request Review
by: Zhang, Daoan, et al.
Published: (2026)
by: Zhang, Daoan, et al.
Published: (2026)
Is Next Token Prediction Sufficient for GPT? Exploration on Code Logic Comprehension
by: Qi, Mengnan, et al.
Published: (2024)
by: Qi, Mengnan, et al.
Published: (2024)
SWE-bench Goes Live!
by: Zhang, Linghao, et al.
Published: (2025)
by: Zhang, Linghao, et al.
Published: (2025)
DI-BENCH: Benchmarking Large Language Models on Dependency Inference with Testable Repositories at Scale
by: Zhang, Linghao, et al.
Published: (2025)
by: Zhang, Linghao, et al.
Published: (2025)
ORACLE-SWE: Quantifying the Contribution of Oracle Information Signals on SWE Agents
by: Li, Kenan, et al.
Published: (2026)
by: Li, Kenan, et al.
Published: (2026)
Agentic Harness Engineering: Observability-Driven Automatic Evolution of Coding-Agent Harnesses
by: Lin, Jiahang, et al.
Published: (2026)
by: Lin, Jiahang, et al.
Published: (2026)
Code-Vision: Evaluating Multimodal LLMs Logic Understanding and Code Generation Capabilities
by: Wang, Hanbin, et al.
Published: (2025)
by: Wang, Hanbin, et al.
Published: (2025)
Evaluating the Generalization Capabilities of Large Language Models on Code Reasoning
by: Yang, Rem, et al.
Published: (2025)
by: Yang, Rem, et al.
Published: (2025)
AutoCode: LLMs as Problem Setters for Competitive Programming
by: Zhou, Shang, et al.
Published: (2025)
by: Zhou, Shang, et al.
Published: (2025)
PerfCodeBench: Benchmarking LLMs for System-Level High-Performance Code Optimization
by: Jing, Huihao, et al.
Published: (2026)
by: Jing, Huihao, et al.
Published: (2026)
Humanity's Last Code Exam: Can Advanced LLMs Conquer Human's Hardest Code Competition?
by: Li, Xiangyang, et al.
Published: (2025)
by: Li, Xiangyang, et al.
Published: (2025)
Showing LLM-Generated Code Selectively Based on Confidence of LLMs
by: Li, Jia, et al.
Published: (2024)
by: Li, Jia, et al.
Published: (2024)
Code Repair with LLMs gives an Exploration-Exploitation Tradeoff
by: Tang, Hao, et al.
Published: (2024)
by: Tang, Hao, et al.
Published: (2024)
Evaluation of Code LLMs on Geospatial Code Generation
by: Gramacki, Piotr, et al.
Published: (2024)
by: Gramacki, Piotr, et al.
Published: (2024)
Agentic Code Reasoning
by: Ugare, Shubham, et al.
Published: (2026)
by: Ugare, Shubham, et al.
Published: (2026)
Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI
by: Sapkota, Ranjan, et al.
Published: (2025)
by: Sapkota, Ranjan, et al.
Published: (2025)
CodeSpecBench: Benchmarking LLMs for Executable Behavioral Specification Generation
by: Chen, Zaoyu, et al.
Published: (2026)
by: Chen, Zaoyu, et al.
Published: (2026)
Automatically Benchmarking LLM Code Agents through Agent-Driven Annotation and Evaluation
by: Fu, Lingyue, et al.
Published: (2025)
by: Fu, Lingyue, et al.
Published: (2025)
CodeIF-Bench: Evaluating Instruction-Following Capabilities of Large Language Models in Interactive Code Generation
by: Wang, Peiding, et al.
Published: (2025)
by: Wang, Peiding, et al.
Published: (2025)
From Effectiveness to Efficiency: Uncovering Linguistic Bias in Large Language Model-based Code Generation
by: Jiang, Weipeng, et al.
Published: (2024)
by: Jiang, Weipeng, et al.
Published: (2024)
Enhancing Code LLMs with Reinforcement Learning in Code Generation: A Survey
by: Wang, Junqiao, et al.
Published: (2024)
by: Wang, Junqiao, et al.
Published: (2024)
ContextEcho: A Benchmark for Persona Drift in Long Agentic-Coding Sessions
by: Ding, Xianzhong, et al.
Published: (2026)
by: Ding, Xianzhong, et al.
Published: (2026)
CodeHalu: Investigating Code Hallucinations in LLMs via Execution-based Verification
by: Tian, Yuchen, et al.
Published: (2024)
by: Tian, Yuchen, et al.
Published: (2024)
CodePod: A Language-Agnostic Hierarchical Scoping System for Interactive Development
by: Li, Hebi, et al.
Published: (2023)
by: Li, Hebi, et al.
Published: (2023)
GameDevBench: Evaluating Agentic Capabilities Through Game Development
by: Chi, Wayne, et al.
Published: (2026)
by: Chi, Wayne, et al.
Published: (2026)
DARS: Dynamic Action Re-Sampling to Enhance Coding Agent Performance by Adaptive Tree Traversal
by: Aggarwal, Vaibhav, et al.
Published: (2025)
by: Aggarwal, Vaibhav, et al.
Published: (2025)
AetherCode: Evaluating LLMs' Ability to Win In Premier Programming Competitions
by: Wang, Zihan, et al.
Published: (2025)
by: Wang, Zihan, et al.
Published: (2025)
OpenCodeInstruct: A Large-scale Instruction Tuning Dataset for Code LLMs
by: Ahmad, Wasi Uddin, et al.
Published: (2025)
by: Ahmad, Wasi Uddin, et al.
Published: (2025)
Code Broker: A Multi-Agent System for Automated Code Quality Assessment
by: Attrah, Samer
Published: (2026)
by: Attrah, Samer
Published: (2026)
Iterative Refinement of Project-Level Code Context for Precise Code Generation with Compiler Feedback
by: Bi, Zhangqian, et al.
Published: (2024)
by: Bi, Zhangqian, et al.
Published: (2024)
Generating Equivalent Representations of Code By A Self-Reflection Approach
by: Li, Jia, et al.
Published: (2024)
by: Li, Jia, et al.
Published: (2024)
NLPerturbator: Studying the Robustness of Code LLMs to Natural Language Variations
by: Chen, Junkai, et al.
Published: (2024)
by: Chen, Junkai, et al.
Published: (2024)
Model Editing for LLMs4Code: How Far are We?
by: Li, Xiaopeng, et al.
Published: (2024)
by: Li, Xiaopeng, et al.
Published: (2024)
FairCoder: Evaluating Social Bias of LLMs in Code Generation
by: Du, Yongkang, et al.
Published: (2025)
by: Du, Yongkang, et al.
Published: (2025)
Coffee: Boost Your Code LLMs by Fixing Bugs with Feedback
by: Moon, Seungjun, et al.
Published: (2023)
by: Moon, Seungjun, et al.
Published: (2023)
AgentPack: A Dataset of Code Changes, Co-Authored by Agents and Humans
by: Zi, Yangtian, et al.
Published: (2025)
by: Zi, Yangtian, et al.
Published: (2025)
Is Vibe Coding Safe? Benchmarking Vulnerability of Agent-Generated Code in Real-World Tasks
by: Zhao, Songwen, et al.
Published: (2025)
by: Zhao, Songwen, et al.
Published: (2025)
From Code Foundation Models to Agents and Applications: A Comprehensive Survey and Practical Guide to Code Intelligence
by: Yang, Jian, et al.
Published: (2025)
by: Yang, Jian, et al.
Published: (2025)
SceneGenAgent: Precise Industrial Scene Generation with Coding Agent
by: Xia, Xiao, et al.
Published: (2024)
by: Xia, Xiao, et al.
Published: (2024)
Beyond Accuracy: A Cognitive Load Framework for Mapping the Capability Boundaries of Tool-use Agents
by: Wang, Qihao, et al.
Published: (2026)
by: Wang, Qihao, et al.
Published: (2026)
Similar Items
-
Sphinx: Benchmarking and Modeling for LLM-Driven Pull Request Review
by: Zhang, Daoan, et al.
Published: (2026) -
Is Next Token Prediction Sufficient for GPT? Exploration on Code Logic Comprehension
by: Qi, Mengnan, et al.
Published: (2024) -
SWE-bench Goes Live!
by: Zhang, Linghao, et al.
Published: (2025) -
DI-BENCH: Benchmarking Large Language Models on Dependency Inference with Testable Repositories at Scale
by: Zhang, Linghao, et al.
Published: (2025) -
ORACLE-SWE: Quantifying the Contribution of Oracle Information Signals on SWE Agents
by: Li, Kenan, et al.
Published: (2026)