collaborators

7 papers

econ.TH2026

Revealing Structured Heterogeneity

Christopher Turansick

In this paper, we study models of restricted heterogeneity. While the random utility model allows for arbitrary heterogeneity among rational types, we consider the case when an ana…

cs.AI2026

The Granularity Axis: A Micro-to-Macro Latent Direction for Social Roles in Language Models

Chonghan Qin, Xiachong Feng, Ziyun Song +3

Large language models (LLMs) are routinely prompted to take on social roles ranging from individuals to institutions, yet it remains unclear whether their internal representations…

cs.AI2026

SAVOIR: Learning Social Savoir-Faire via Shapley-based Reward Attribution

Xiachong Feng, Yi Jiang, Xiaocheng Feng +9

Social intelligence, the ability to navigate complex interpersonal interactions, presents a fundamental challenge for language agents. Training such agents via reinforcement learni…

cs.AI2026

ImplicitMemBench: Measuring Unconscious Behavioral Adaptation in Large Language Models

Chonghan Qin, Xiachong Feng, Weitao Ma +2

Existing memory benchmarks for LLM agents evaluate explicit recall of facts, yet overlook implicit memory where experience becomes automated behavior without conscious retrieval. T…

cs.CV2026

MMFineReason: Closing the Multimodal Reasoning Gap via Open Data-Centric Methods

Honglin Lin, Zheng Liu, Yun Zhu +6

Recent advances in Vision Language Models (VLMs) have driven significant progress in visual reasoning. However, open-source VLMs still lag behind proprietary systems, largely due t…

cs.CV2026

Scientific Image Synthesis: Benchmarking, Methodologies, and Downstream Utility

Honglin Lin, Zheng Liu, Chonghan Qin +7

While synthetic data has proven effective for improving scientific reasoning in the text domain, multimodal reasoning remains constrained by the difficulty of synthesizing scientif…

cs.CV2026

ChartVerse: Scaling Chart Reasoning via Reliable Programmatic Synthesis from Scratch

Zheng Liu, Honglin Lin, Chonghan Qin +13

Chart reasoning is a critical capability for Vision Language Models (VLMs). However, the development of open-source models is severely hindered by the lack of high-quality training…