paper.dinq.meAI 与前沿科学顶会 · 学术新星雷达
登录 DINQ
返回新星榜
SK

Santu Karmaker

ACL 2026×2NeurIPS 2026×2评测与基准推理理论与学习动力学代码智能体与工具
新星分资深
25
一作贡献0
核心/参与10
方向广度13
合作网络6
0 一作 · 4 篇 · ACL 2026 / NeurIPS 2026

获取完整研究档案

首次获取该候选人的完整档案及 StartLux 评估共 20 积分;每位用户单独解锁,之后查看免费。主动刷新 20 积分。

联系方式

实时查找电子邮箱,费用不超过20积分;未找到邮箱不扣费。

2026 顶会论文

4
作者位次 #3/4ACL 2026Poster· Natural Language Processing

The Path Not Taken: Duality in Reasoning about Program Execution

Eshgin Hasanov · Md Mahadi Hassan Sibat · Santu Karmaker · Aashish Yadavally

摘要

Large language models (LLMs) have shown remarkable capabilities across diverse coding tasks. However, their adoption requires a true understanding of program execution rather than relying on surface-level patterns. Existing benchmarks primarily focus on predicting program properties tied to speci...

评测与基准代码推理OpenReview 项目页
作者位次 #4/4ACL 2026Findings· Findings of ACL

Large Language Models for IT Automation Tasks: Are We There Yet?

Md Mahadi Hassan Sibat · John Salvador · Akond Rahman · Santu Karmaker

摘要

LLMs show promise in code generation, yet their effectiveness for IT automation tasks, particularly for tools like Ansible, remains understudied. Existing benchmarks rely primarily on synthetic tasks that fail to capture the needs of practitioners who use IT automation tools. We present ExITBench...

评测与基准推理智能体与工具OpenReview 项目页

常见合作者