3 citations · 8 across the 23 of their papers we have counts for
7 papers · 1 filter
ONNX-Net: Towards Universal Representations and Instant Performance Prediction for Neural Architectures
Shiwen Qin, Alexander Auras, Shay B. Cohen +4
Neural architecture search (NAS) automates the design process of high-performing architectures, but remains bottlenecked by expensive performance evaluation. Most existing studies…
PiCSAR: Probabilistic Confidence Selection And Ranking for Reasoning Chains
Joshua Ong Jun Leang, Zheng Zhao, Aryo Pradipta Gema +7
Best-of-n sampling improves the accuracy of large language models (LLMs) and large reasoning models (LRMs) by generating multiple candidate solutions and selecting the one with the…
PersonaLens: A Benchmark for Personalization Evaluation in Conversational AI Assistants
Zheng Zhao, Clara Vania, Subhradeep Kayal +3
Large language models (LLMs) have advanced conversational AI assistants. However, systematically evaluating how well these assistants apply personalization--adapting to individual…
Iterative Multilingual Spectral Attribute Erasure
Shun Shao, Yftah Ziser, Zheng Zhao +3
Multilingual representations embed words with similar meanings to share a common semantic space across languages, creating opportunities to transfer debiasing effects between langu…
Can VLMs Predict Future States? Bootstrapping World Models from Inverse Dynamics
Yifu Qiu, Yftah Ziser, Anna Korhonen +2
Can unified vision-language models (VLMs) perform forward dynamics prediction (FDP), i.e., predicting the future state (in image form) given the previous observation and an action…
Transferrable Surrogates in Expressive Neural Architecture Search Spaces
Shiwen Qin, Gabriela Kadlecová, Martin Pilát +5
Neural architecture search (NAS) faces a challenge in balancing the exploration of expressive, broad search spaces that enable architectural innovation with the need for efficient…
Eliciting In-context Retrieval and Reasoning for Long-context Large Language Models
Yifu Qiu, Varun Embar, Yizhe Zhang +3
Recent advancements in long-context language models (LCLMs) promise to transform Retrieval-Augmented Generation (RAG) by simplifying pipelines. With their expanded context windows,…