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Learning What Matters: Dynamic Dimension Selection and Aggregation for Interpretable Vision-Language Reward Modeling
Qiyuan Chen, Hongsen Huang, Jiahe Chen +6
Vision-language reward modeling faces a dilemma: generative approaches are interpretable but slow, while discriminative ones are efficient but act as opaque "black boxes." To bridg…
Icon: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation
Qiyuan Chen, Hongsen Huang, Qian Shao +6
Large Language Models (LLMs) require high quality preference datasets to align with human preferences. However, conventional methods for constructing such datasets face significant…
CC-GSEO-Bench: A Content-Centric Benchmark for Measuring Source Influence in Generative Search Engines
Qiyuan Chen, Jiahe Chen, Hongsen Huang +7
Generative Search Engines (GSEs) synthesize conversational answers from multiple sources, weakening the long-standing link between search ranking and digital visibility. This shift…
Mind's Mirror: Distilling Self-Evaluation Capability and Comprehensive Thinking from Large Language Models
Weize Liu, Guocong Li, Kai Zhang +6
Large language models (LLMs) have achieved remarkable advancements in natural language processing. However, the massive scale and computational demands of these models present form…