activity
20182026
most citedLanguage Model as an Annotator: Exploring DialoGPT for Dialogue Summarization

10 citations · 19 across the 28 of their papers we have counts for

collaborators

45 papers

cs.CL2026

Culture-Aware Machine Translation in Large Language Models: Benchmarking and Investigation

Zekun Yuan, Yangfan Ye, Xiaocheng Feng +5

Large language models (LLMs) have achieved strong performance in general machine translation, yet their ability in culture-aware scenarios remains poorly understood. To bridge this…

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

Stratagem: Learning Transferable Reasoning via Trajectory-Modulated Game Self-Play

Xiachong Feng, Deyi Yin, Xiaocheng Feng +9

Games offer a compelling paradigm for developing general reasoning capabilities in language models, as they naturally demand strategic planning, probabilistic inference, and adapti…

cs.CL2026

x1: Learning to Think Adaptively Across Languages and Cultures

Yangfan Ye, Xiaocheng Feng, Xiachong Feng +8

Languages encode distinct abstractions and inductive priors, yet most large language models (LLMs) overlook this diversity by reasoning in a single dominant language. In this work,…

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.AI2026

Not All Tokens See Equally: Perception-Grounded Policy Optimization for Large Vision-Language Models

Zekai Ye, Qiming Li, Xiaocheng Feng +6

While Reinforcement Learning from Verifiable Rewards (RLVR) has advanced reasoning in Large Vision-Language Models (LVLMs), prevailing frameworks suffer from a foundational methodo…