5 citations · 11 across the 11 of their papers we have counts for
11 papers
EvidenT: Building Trustworthy Enterprise Assistants through Evidence Groundedness and Traceability
Anubha Kabra, Katie Jooyoung Kim, Colin Zhiwei Kou +5
Enterprise AI assistants must produce responses that are verifiable and traceable to source evidence. However, retrieval augmented generation (RAG) over heterogeneous enterprise da…
Measuring, Modeling, and Helping People Account for Privacy Risks in Online Self-Disclosures with AI
Isadora Krsek, Anubha Kabra, Yao Dou +5
In pseudonymous online fora like Reddit, the benefits of self-disclosure are often apparent to users (e.g., I can vent about my in-laws to understanding strangers), but the privacy…
AI-LieDar: Examine the Trade-off Between Utility and Truthfulness in LLM Agents
Zhe Su, Xuhui Zhou, Sanketh Rangreji +4
Truthfulness (adherence to factual accuracy) and utility (satisfying human needs and instructions) are both fundamental aspects of Large Language Models, yet these goals often conf…
Program-Aided Reasoners (better) Know What They Know
Anubha Kabra, Sanketh Rangreji, Yash Mathur +3
Prior work shows that program-aided reasoning, in which large language models (LLMs) are combined with programs written in programming languages such as Python, can significantly i…
Reducing Privacy Risks in Online Self-Disclosures with Language Models
Yao Dou, Isadora Krsek, Tarek Naous +4
Self-disclosure, while being common and rewarding in social media interaction, also poses privacy risks. In this paper, we take the initiative to protect the user-side privacy asso…
Counting the Bugs in ChatGPT's Wugs: A Multilingual Investigation into the Morphological Capabilities of a Large Language Model
Leonie Weissweiler, Valentin Hofmann, Anjali Kantharuban +10
Large language models (LLMs) have recently reached an impressive level of linguistic capability, prompting comparisons with human language skills. However, there have been relative…
Multi-lingual and Multi-cultural Figurative Language Understanding
Anubha Kabra, Emmy Liu, Simran Khanuja +6
Figurative language permeates human communication, but at the same time is relatively understudied in NLP. Datasets have been created in English to accelerate progress towards meas…
Ceasing hate withMoH: Hate Speech Detection in Hindi-English Code-Switched Language
Arushi Sharma, Anubha Kabra, Minni Jain
Social media has become a bedrock for people to voice their opinions worldwide. Due to the greater sense of freedom with the anonymity feature, it is possible to disregard social e…
Cluster Based Deep Contextual Reinforcement Learning for top-k Recommendations
Anubha Kabra, Anu Agarwal, Anil Singh Parihar
Rapid advancements in the E-commerce sector over the last few decades have led to an imminent need for personalised, efficient and dynamic recommendation systems. To sufficiently c…
MixBoost: Synthetic Oversampling with Boosted Mixup for Handling Extreme Imbalance
Anubha Kabra, Ayush Chopra, Nikaash Puri +4
Training a classification model on a dataset where the instances of one class outnumber those of the other class is a challenging problem. Such imbalanced datasets are standard in…
Evaluation Toolkit For Robustness Testing Of Automatic Essay Scoring Systems
Anubha Kabra, Mehar Bhatia, Yaman Kumar +2
Automatic scoring engines have been used for scoring approximately fifteen million test-takers in just the last three years. This number is increasing further due to COVID-19 and t…