Colpali: Efficient document retrieval with vision language models
Documents are visually rich structures that convey information through text, as well as
tables, figures, page layouts, or fonts. While modern document retrieval systems exhibit …
tables, figures, page layouts, or fonts. While modern document retrieval systems exhibit …
VERISCORE: Evaluating the factuality of verifiable claims in long-form text generation
Existing metrics for evaluating the factuality of long-form text, such as FACTSCORE (Min et
al., 2023) and SAFE (Wei et al., 2024), decompose an input text into" atomic claims" and …
al., 2023) and SAFE (Wei et al., 2024), decompose an input text into" atomic claims" and …
Auxiliary task demands mask the capabilities of smaller language models
Developmental psychologists have argued about when cognitive capacities such as
language understanding or theory of mind emerge. These debates often hinge on the …
language understanding or theory of mind emerge. These debates often hinge on the …
Evaluating language models as risk scores
Current question-answering benchmarks predominantly focus on accuracy in realizable
prediction tasks. Conditioned on a question and answer-key, does the most likely token …
prediction tasks. Conditioned on a question and answer-key, does the most likely token …
Enhancing logical reasoning in large language models through graph-based synthetic data
Despite recent advances in training and prompting strategies for Large Language Models
(LLMs), these models continue to face challenges with complex logical reasoning tasks that …
(LLMs), these models continue to face challenges with complex logical reasoning tasks that …
Fast State Restoration in LLM Serving with HCache
The growing complexity of LLM usage today, eg, multi-round conversation and retrieval-
augmented generation (RAG), makes contextual states (ie, KV cache) reusable across user …
augmented generation (RAG), makes contextual states (ie, KV cache) reusable across user …
Sorsa: Singular values and orthonormal regularized singular vectors adaptation of large language models
Y Cao - arXiv preprint arXiv:2409.00055, 2024 - arxiv.org
The rapid advancement in large language models (LLMs) comes with a significant increase
in their parameter size, presenting challenges for adaptation and fine-tuning. Parameter …
in their parameter size, presenting challenges for adaptation and fine-tuning. Parameter …
Automated Text Scoring in the Age of Generative AI for the GPU-poor
CM Ormerod, A Kwako - arXiv preprint arXiv:2407.01873, 2024 - arxiv.org
Current research on generative language models (GLMs) for automated text scoring (ATS)
has focused almost exclusively on querying proprietary models via Application …
has focused almost exclusively on querying proprietary models via Application …
OpenT2T: An Open-Source Toolkit for Table-to-Text Generation
Table data is pervasive in various industries, and its comprehension and manipulation
demand significant time and effort for users seeking to extract relevant information …
demand significant time and effort for users seeking to extract relevant information …
OntoType: Ontology-Guided and Pre-Trained Language Model Assisted Fine-Grained Entity Typing
Fine-grained entity typing (FET), which assigns entities in text with context-sensitive, fine-
grained semantic types, is a basic but important task for knowledge extraction from …
grained semantic types, is a basic but important task for knowledge extraction from …