3 papers
cs.CL2026
Last Translation Benchmark
Vilém Zouhar, Niyati Bafna, Mukund Choudhary +241
For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation methods that inform us about failure cases. As models get stronger, stan…
cs.CL2026
Reading, Not Thinking: Understanding and Bridging the Modality Gap When Text Becomes Pixels in Multimodal LLMs
Kaiser Sun, Xiaochuang Yuan, Hongjun Liu +4
Multimodal large language models (MLLMs) can process text presented as images, yet they often perform worse than when the same content is provided as textual tokens. We systematica…
cs.AI2026
TraderBench: How Robust Are AI Agents in Adversarial Capital Markets?
Xiaochuang Yuan, Hui Xu, Silvia Xu +2
Evaluating AI agents in finance faces two key challenges: static benchmarks require costly expert annotation yet miss the dynamic decision-making central to real-world trading, whi…