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Chirag Shah

ACL 2026×2ICML 2026评测与基准多模态代码社会与人本对齐与偏好
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0 一作 · 3 篇 · ACL 2026 / ICML 2026

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2026 顶会论文

3
作者位次 #3/3ICML 2026Poster· Applications / Language, Speech and Dialog

Position: Knowing Isn’t Understanding: Re-grounding Generative Proactivity with Epistemic and Behavioral Insight

Kirandeep Kaur · Xingda Lyu · Chirag Shah

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

C laim DB : A Fact Verification Benchmark over Large Structured Data

Michael Theologitis · Preetam Prabhu Srikar Dammu · Chirag Shah · Dan Suciu

摘要

Real-world fact-checking often involves verifying claims grounded in structured data at scale. Despite substantial progress in fact-verification benchmarks, this setting remains largely underexplored. In this work, we introduce ClaimDB, a fact-verification benchmark where the evidence for claims...

评测与基准代码社会与人本OpenReview 项目页
作者位次 #4/4ACL 2026Findings· Findings of ACL

PROPER Agents: Proactivity Driven Personalized Agents for Advancing Knowledge Gap Navigation

Kirandeep Kaur · Vinayak Gupta · Aditya Gupta · Chirag Shah

摘要

Current approaches to proactive assistance move beyond the ask-and-respond paradigm by anticipating user needs. In practice, they either burden users with clarifying questions or rely on context-based extrapolation, often leading to unnecessary or mistimed interventions. Such systems lack explici...

对齐与偏好评测与基准检索与知识OpenReview 项目页

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