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20162026
most citedHierarchical Transformers for Multi-Document Summarization

34 citations · 160 across the 32 of their papers we have counts for

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cs.AI2026

A Table Is Worth 64 Tokens: Pixel-level Compression for Multi-Table Document Question Answering

Iñigo Alonso, Mirella Lapata

Answering questions over real-world documents requires processing long inputs that interleave text with tables. Optical context compression, which represents context as images, pro…

cs.AI2026

Pandora's AI Model Routing Box: Efficient Allocation with Costly Value Estimation

Adam Fisch, Shubhendu Trivedi, Fantine Huot +5

Heterogeneous AI systems composed of multiple models, architectures, harnesses, or inference-time settings can improve quality and efficiency by routing queries to the specialist w…

cs.AI2025

Meta-Adaptive Prompt Distillation for Few-Shot Visual Question Answering

Akash Gupta, Amos Storkey, Mirella Lapata

Large Multimodal Models (LMMs) often rely on in-context learning (ICL) to perform new visual question answering (VQA) tasks with minimal supervision. However, ICL performance, espe…

cs.AI2025

Debating for Better Reasoning: An Unsupervised Multimodal Approach

Ashutosh Adhikari, Mirella Lapata

As Large Language Models (LLMs) gain expertise across diverse domains and modalities, scalable oversight becomes increasingly challenging, particularly when their capabilities may…

cs.AI2024

ScreenWriter: Automatic Screenplay Generation and Movie Summarisation

Louis Mahon, Mirella Lapata

The proliferation of creative video content has driven demand for textual descriptions or summaries that allow users to recall key plot points or get an overview without watching.…