44 citations · 123 across the 45 of their papers we have counts for
47 papers · 1 filter
Learning to Control Summaries with Score Ranking
Hongye Liu, Liang Ding, Ricardo Henao
Recent advances in summarization research focus on improving summary quality across multiple criteria, such as completeness, conciseness, and faithfulness, by jointly optimizing th…
Think Dense, Not Long: Dynamic Decoupled Conditional Advantage for Efficient Reasoning
Keqin Peng, Yuanxin Ouyang, Xuebo Liu +4
Reinforcement Learning with Verifiable Rewards (RLVR) can elicit strong multi-step reasoning, yet it often encourages overly verbose traces. Moreover, naive length penalties in gro…
The Bitter Lesson of Diffusion Language Models for Agentic Workflows: A Comprehensive Reality Check
Qingyu Lu, Liang Ding, Kanjian Zhang +2
The pursuit of real-time agentic interaction has driven interest in Diffusion-based Large Language Models (dLLMs) as alternatives to auto-regressive backbones, promising to break t…
Reason-KE++: Aligning the Process, Not Just the Outcome, for Faithful LLM Knowledge Editing
Yuchen Wu, Liang Ding, Li Shen +1
Aligning Large Language Models (LLMs) to be faithful to new knowledge in complex, multi-hop reasoning tasks is a critical, yet unsolved, challenge. We find that SFT-based methods,…
Robust Knowledge Editing via Explicit Reasoning Chains for Distractor-Resilient Multi-Hop QA
Yuchen Wu, Liang Ding, Li Shen +1
Large language models (LLMs) encode vast amounts of world knowledge but remain static once trained, making the timely integration of emerging facts prohibitively expensive via full…
Revisiting Overthinking in Long Chain-of-Thought from the Perspective of Self-Doubt
Keqin Peng, Liang Ding, Yuanxin Ouyang +2
Reasoning Large Language Models (RLLMs) have demonstrated impressive performance on complex tasks, largely due to the adoption of Long Chain-of-Thought (Long CoT) reasoning. Howeve…