most citedInvestigating the Role of Centering Theory in the Context of Neural Coreference Resolution Systems

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cs.CL2025

Towards Faithful and Controllable Personalization via Critique-Post-Edit Reinforcement Learning

Chenghao Zhu, Meiling Tao, Tiannan Wang +3

Faithfully personalizing large language models (LLMs) to align with individual user preferences is a critical but challenging task. While supervised fine-tuning (SFT) quickly reach…

cs.CL2025

AFM: An Adaptive Agent Foundation Model for Tool-Aware Hybrid Reasoning

Qianben Chen, Jingyi Cao, Jiayu Zhang +12

Large language models split into two families: reasoning-centric LLMs, which strengthen internal chain-of-thought reasoning but cannot invoke external tools, and agentic LLMs, whic…

cs.CL2025

ACADREASON: Exploring the Limits of Reasoning Models with Academic Research Problems

Xin Gui, King Zhu, JinCheng Ren +17

In recent years, the research focus of large language models (LLMs) and agents has shifted increasingly from demonstrating novel capabilities to complex reasoning and tackling chal…

cs.CL2022

Autoregressive Structured Prediction with Language Models

Tianyu Liu, Yuchen Jiang, Nicholas Monath +2

Recent years have seen a paradigm shift in NLP towards using pretrained language models ({PLM}) for a wide range of tasks. However, there are many difficult design decisions to rep…

cs.CL20221 cited

Investigating the Role of Centering Theory in the Context of Neural Coreference Resolution Systems

Yuchen Eleanor Jiang, Ryan Cotterell, Mrinmaya Sachan

Centering theory (CT; Grosz et al., 1995) provides a linguistic analysis of the structure of discourse. According to the theory, local coherence of discourse arises from the manner…

cs.CL2022

A Bilingual Parallel Corpus with Discourse Annotations

Yuchen Eleanor Jiang, Tianyu Liu, Shuming Ma +3

Machine translation (MT) has almost achieved human parity at sentence-level translation. In response, the MT community has, in part, shifted its focus to document-level translation…