activity
20232026
most citedNoveltyBench: Evaluating Language Models for Humanlike Diversity

1 citations · 2 across the 7 of their papers we have counts for

collaborators

8 papers

cs.AI2026

GeoAgent: Learning to Geolocate Everywhere with Reinforced Geographic Characteristics

Modi Jin, Yiming Zhang, Boyuan Sun +3

This paper presents GeoAgent, a model capable of reasoning closely with humans and deriving fine-grained address conclusions. Previous RL-based methods have achieved breakthroughs…

cs.CV2026

Multimodal Latent Reasoning via Hierarchical Visual Cues Injection

Yiming Zhang, Qiangyu Yan, Borui Jiang +1

The advancement of multimodal large language models (MLLMs) has enabled impressive perception capabilities. However, their reasoning process often remains a "fast thinking" paradig…

cs.LG2025

Multi-Scale Finetuning for Encoder-based Time Series Foundation Models

Zhongzheng Qiao, Chenghao Liu, Yiming Zhang +6

Time series foundation models (TSFMs) demonstrate impressive zero-shot performance for time series forecasting. However, an important yet underexplored challenge is how to effectiv…

cs.CL2025

CIE: Controlling Language Model Text Generations Using Continuous Signals

Vinay Samuel, Harshita Diddee, Yiming Zhang +1

Aligning language models (LMs) with user intent is becoming increasingly relevant to enhance user experience. This calls for designing methods that can allow users to control the p…

cs.LG2025

The Estimation of Continual Causal Effect for Dataset Shifting Streams

Baining Chen, Yiming Zhang, Yuqiao Han +6

Causal effect estimation has been widely used in marketing optimization. The framework of an uplift model followed by a constrained optimization algorithm is popular in practice. T…

cs.CL2025★ 1 cited

NoveltyBench: Evaluating Language Models for Humanlike Diversity

Yiming Zhang, Harshita Diddee, Susan Holm +5

Language models have demonstrated remarkable capabilities on standard benchmarks, yet they struggle increasingly from mode collapse, the inability to generate diverse and novel out…

cs.LG2025

Towards Large-Scale In-Context Reinforcement Learning by Meta-Training in Randomized Worlds

Fan Wang, Pengtao Shao, Yiming Zhang +6

In-Context Reinforcement Learning (ICRL) enables agents to learn automatically and on-the-fly from their interactive experiences. However, a major challenge in scaling up ICRL is t…

cs.AI2023★ 1 cited

Emergent Communication in Interactive Sketch Question Answering

Zixing Lei, Yiming Zhang, Yuxin Xiong +1

Vision-based emergent communication (EC) aims to learn to communicate through sketches and demystify the evolution of human communication. Ironically, previous works neglect multi-…