1 citations · 1 across the 10 of their papers we have counts for
10 papers
PILA: Plug-and-Play Insertion for LLM-native Advertising
Zhaowei Zhang, Yuhan Fu, Yihang Zhang +6
How to monetize large language models (LLMs) by naturally integrating sponsored content into their responses, known as LLM-native advertising, has recently emerged as a critical pr…
Data-driven Head Motion Generation through Natural Gaze-Head Coordination
Xiaohan Liu, Yilin Wen, Yusuke Sugano
We present the first data-driven approach to model temporal gaze-head coordination from large-scale in-the-wild facial videos. To obtain training data for generalizable learning, w…
TRACER: Verifiable Generative Provenance for Multimodal Tool-Using Agents
Bihui Yu, Caijun Jia, Jing Chi +6
Multimodal large language models increasingly solve vision-centric tasks by calling external tools for visual inspection, OCR, retrieval, calculation, and multi-step reasoning. Cur…
Adam's Law: Textual Frequency Law on Large Language Models
Hongyuan Adam Lu, Z. L., Victor Wei +5
While textual frequency has been validated as relevant to human cognition in reading speed, its relatedness to Large Language Models (LLMs) is seldom studied. We propose a novel re…
Does LLM Alignment Really Need Diversity? An Empirical Study of Adapting RLVR Methods for Moral Reasoning
Zhaowei Zhang, Xiaohan Liu, Xuekai Zhu +6
Reinforcement learning with verifiable rewards (RLVR) has achieved remarkable success in logical reasoning tasks, yet whether large language model (LLM) alignment requires fundamen…
Counting Hallucinations in Diffusion Models
Shuai Fu, Jian Zhou, Qi Chen +7
Diffusion probabilistic models (DPMs) have demonstrated remarkable progress in generative tasks, such as image and video synthesis. However, they still often produce hallucinated s…
The Bias is in the Details: An Assessment of Cognitive Bias in LLMs
R. Alexander Knipper, Charles S. Knipper, Kaiqi Zhang +3
As Large Language Models (LLMs) are increasingly embedded in real-world decision-making processes, it becomes crucial to examine the extent to which they exhibit cognitive biases.…
From KMMLU-Redux to KMMLU-Pro: A Professional Korean Benchmark Suite for LLM Evaluation
Seokhee Hong, Sunkyoung Kim, Guijin Son +3
The development of Large Language Models (LLMs) requires robust benchmarks that encompass not only academic domains but also industrial fields to effectively evaluate their applica…
Assay2Mol: large language model-based drug design using BioAssay context
Yifan Deng, Spencer S. Ericksen, Anthony Gitter
Scientific databases aggregate vast amounts of quantitative data alongside descriptive text. In biochemistry, molecule screening assays evaluate candidate molecules' functional res…
RouteNator: A Router-Based Multi-Modal Architecture for Generating Synthetic Training Data for Function Calling LLMs
Vibha Belavadi, Tushar Vatsa, Dewang Sultania +5
This paper addresses fine-tuning Large Language Models (LLMs) for function calling tasks when real user interaction data is unavailable. In digital content creation tools, where us…