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20132026
most citedBring Your Own KG: Self-Supervised Program Synthesis for Zero-Shot KGQA

9 citations · 11 across the 11 of their papers we have counts for

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cs.CL2026

Probing the Prompt KV Cache: Where It Becomes Dispensable

Vinayshekhar Bannihatti Kumar, Manoj Ghuhan Arivazhagan, Disha Makhija +1

Prior KV cache compression schemes empirically demonstrate that the prompt cache is partially redundant during decoding, dropping or summarising entries with little accuracy loss.…

cs.CL2026

Syntax Without Semantics: Teaching Large Language Models to Code in an Unseen Language

Vinayshekhar Bannihatti Kumar, Disha Makhija, Manoj Ghuhan Arivazhagan +1

Large language models (LLMs) achieve high pass rates on code generation benchmarks, yet whether they can transfer this ability to languages absent from pretraining remains poorly u…

cs.CL2025

When Facts Change: Probing LLMs on Evolving Knowledge with evolveQA

Nishanth Sridhar Nakshatri, Shamik Roy, Manoj Ghuhan Arivazhagan +3

LLMs often fail to handle temporal knowledge conflicts--contradictions arising when facts evolve over time within their training data. Existing studies evaluate this phenomenon thr…

cs.CL2025

When Users Are Happy but Agents Are Wrong: Multi-Dimensional Evaluation of Tool-Augmented Dialogue

Tanya Shourya, Yingfan Wang, Zhaoyi Joey Hou +3

Evaluating conversational AI systems that use external tools is challenging, as errors can arise from complex interactions among user, agent, and tools. While existing evaluation m…

cs.CL2024

Constrained Decoding with Speculative Lookaheads

Nishanth Nakshatri, Shamik Roy, Rajarshi Das +3

Constrained decoding with lookahead heuristics (CDLH) is a highly effective method for aligning LLM generations to human preferences. However, the extensive lookahead roll-out oper…

cs.CL2023★ 9 cited

Bring Your Own KG: Self-Supervised Program Synthesis for Zero-Shot KGQA

Dhruv Agarwal, Rajarshi Das, Sopan Khosla +1

We present BYOKG, a universal question-answering (QA) system that can operate on any knowledge graph (KG), requires no human-annotated training data, and can be ready to use within…

cs.CL2022

Privacy Adhering Machine Un-learning in NLP

Vinayshekhar Bannihatti Kumar, Rashmi Gangadharaiah, Dan Roth

Regulations introduced by General Data Protection Regulation (GDPR) in the EU or California Consumer Privacy Act (CCPA) in the US have included provisions on the \textit{right to b…

cs.CL2022★ 1 cited

Unsupervised Neural Stylistic Text Generation using Transfer learning and Adapters

Vinayshekhar Bannihatti Kumar, Rashmi Gangadharaiah, Dan Roth

Research has shown that personality is a key driver to improve engagement and user experience in conversational systems. Conversational agents should also maintain a consistent per…

cs.CL2013

Exploring the Role of Logically Related Non-Question Phrases for Answering Why-Questions

Niraj Kumar, Rashmi Gangadharaiah, Kannan Srinathan +1

In this paper, we show that certain phrases although not present in a given question/query, play a very important role in answering the question. Exploring the role of such phrases…