Papers by Junan Chen
DynamicFocalPO: Adaptive Focusing Strategy for Preference Optimization (2026.findings-acl)
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| Challenge: | Recent preference optimization algorithms such as Direct Preference Optimization (DPO) have become prevalent for aligning large language models with human preferences. |
| Approach: | They propose a preference optimization algorithm that introduces a modulating factor that down-weighs misranked preference pairs and employs focusing strategy that adapts over the course of training. |
| Outcome: | Experiments show that DynamicFocalPO surpasses both DPO and FocalPO on benchmarks including Alpaca Eval 2.0 and Arena-Hard using Mistral-Base-7B and Llama-3-Instruct-8B. |
Speech Discrete Tokens or Continuous Features? A Comparative Analysis for Spoken Language Understanding in SpeechLLMs (2025.emnlp-main)
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| Challenge: | Speech Large Language Models (SpeechLLMs) have emerged as dominant speech processing approaches. |
| Approach: | They compare self-supervised learning-based discrete and continuous features . they compare performance across six spoken language understanding-related tasks . |
| Outcome: | The proposed models outperform discrete tokens and continuous features in six spoken language understanding-related tasks. |
When More Thinking Hurts: Overthinking in LLM Test-Time Compute Scaling (2026.findings-acl)
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| Challenge: | Existing research implicitly assumes that longer thinking leads to better results . a recent study suggests that test-time compute scaling is more effective than model scaling . |
| Approach: | They challenge the assumption that longer thinking yields better results . they show that models exhibit overthinking and marginal returns diminish at higher budgets . |
| Outcome: | The proposed framework reduces computation significantly while maintaining comparable accuracy. |