Documents are visually rich structures that convey information through text, but also figures,
page layouts, tables, or even fonts. Since modern retrieval systems mainly rely on the textual …

Developmental psychologists have argued about when cognitive capacities such as
language understanding or theory of mind emerge. These debates often hinge on the …

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 …

We introduce FinanceMath, a novel benchmark designed to evaluate LLMs' capabilities in
solving knowledge-intensive math reasoning problems. Compared to prior works, this study …

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 …

The rise of Large Language Models (LLMs) has accentuated the need for diverse, high-
quality pre-training data. Synthetic data emerges as a viable solution to the challenges of …

Despite the recent breakthroughs achieved by Large Vision Language Models (LVLMs) in
understanding and responding to complex visual-textual contexts, their inherent …

Simultaneous Machine Translation (SiMT) generates translation while reading source
tokens, essentially producing the target prefix based on the source prefix. To achieve good …

Current question-answering benchmarks predominantly focus on accuracy in realizable
prediction tasks. Conditioned on a question and answer-key, does the most likely token …

Current research on generative language models (GLMs) for automated text scoring (ATS)
has focused almost exclusively on querying proprietary models via Application …