1 citations · 2 across the 6 of their papers we have counts for
6 papers
Enginuity: A Dataset and Benchmark for Vision-Language Understanding of Engineering Diagrams
Abhishek Kumar, Isha Motiyani, Tilak Kasturi +3
Engineering diagrams pose a distinct challenge for vision-language models: unlike natural images or general documents, they encode information through dense spatial layouts, domain…
Semantic Alignment of Multilingual Knowledge Graphs via Contextualized Vector Projections
Abhishek Kumar
The paper presents our work on cross-lingual ontology alignment system which uses embedding based cosine similarity matching. The ontology entities are made contextually richer by…
Through the Prism of Culture: Evaluating LLMs' Understanding of Indian Subcultures and Traditions
Garima Chhikara, Abhishek Kumar, Abhijnan Chakraborty
Large Language Models (LLMs) have shown remarkable advancements but also raise concerns about cultural bias, often reflecting dominant narratives at the expense of under-represente…
Found in the Middle: Calibrating Positional Attention Bias Improves Long Context Utilization
Cheng-Yu Hsieh, Yung-Sung Chuang, Chun-Liang Li +8
Large language models (LLMs), even when specifically trained to process long input contexts, struggle to capture relevant information located in the middle of their input. This phe…
Confidence Under the Hood: An Investigation into the Confidence-Probability Alignment in Large Language Models
Abhishek Kumar, Robert Morabito, Sanzhar Umbet +2
As the use of Large Language Models (LLMs) becomes more widespread, understanding their self-evaluation of confidence in generated responses becomes increasingly important as it is…
Subtle Biases Need Subtler Measures: Dual Metrics for Evaluating Representative and Affinity Bias in Large Language Models
Abhishek Kumar, Sarfaroz Yunusov, Ali Emami
Research on Large Language Models (LLMs) has often neglected subtle biases that, although less apparent, can significantly influence the models' outputs toward particular social na…