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

Nandan Thakur

ACL 2026SIGIR 2026评测与基准检索与知识社会与人本可解释性
新星分贡献者
42
一作贡献0
核心/参与10
方向广度11
合作网络9
0 一作 · 2 篇 · ACL 2026 / SIGIR 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

2
作者位次 #17/21ACL 2026Poster· Natural Language Processing

B rowse C omp-Plus: A Fair and Disentangled Evaluation Benchmark for Deep Search Agents

Zijian Chen · Xueguang Ma · Shengyao Zhuang · Ping Nie · Kai Zou · Sahel Sharifymoghaddam · Andrew Liu · Joshua Green · Kshama Patel · Ruoxi Meng · Mingyi Su · Yanxi Li · Haoran Hong · Xinyu Shi · Xuye Liu · Hosna Oyarhoseini · Nandan Thakur · Crystina Zhang · Luyu Gao · Wenhu Chen · Jimmy Lin

摘要

Deep search agents that combine large language models with retrieval tools excel at complex, multi-hop queries. Yet, existing benchmarks such as BrowseComp rely on black-box web search APIs, facing key limitations. (1) Fairness: for agents, dynamic and opaque web APIs hinder reproducibility and f...

评测与基准检索与知识社会与人本OpenReview 项目页
作者位次 #3/6SIGIR 2026Poster· Information Retrieval (Short)

Automating Generation of Long-Form Queries

Shivani Upadhyay · Daniel Campos · Nandan Thakur · Ronak Pradeep · Nick Craswell · Jimmy Lin

摘要

Traditional short keyword queries are increasingly being replaced by longer, more detailed queries that reflect complex and nuanced user information needs, especially in conversational assistants equipped with web search capabilities. In this work, we present a methodology for automatically gener...

检索与知识可解释性评测与基准OpenReview

常见合作者