| Aug 2026 | Our updated ROM paper is now on arXiv. We frame overthinking in large reasoning models as a latent productive-to-redundant transition that is directly decodable from hidden states around first-correct-solution (FCS) boundaries. ROM turns this signal into control: a lightweight streaming detector (~0.1% of backbone parameters) monitors a frozen LRM and intervenes at well-formed reasoning boundaries — no answer extraction, no probe decoding, no backbone updates. Our Counterfactual Self-Correction (CSC) augmentation preserves pre-FCS self-correction. Across five backbones, five benchmarks, and ten baselines under a shared protocol, ROM attains the highest accuracy in 19 of 25 settings, cuts response length 28–77% (mean 45%), and is the only method on the accuracy–length Pareto front in every setting; the same MATH500-trained head transfers zero-shot and cuts wall-clock latency by 46.5%. Check out our project page, code, and dataset. |
| May 2026 | Our new paper PW-OPSD is now on arXiv! We find that teacher-token reliability in on-policy self-distillation for reasoning is position-structured, and propose Position-Weighted On-Policy Self-Distillation (PW-OPSD) to up-weight reliable later tokens at no extra teacher cost. Check out our paper and code. |
| Apr 2026 | Our paper ReasoningBomb has been accepted to ACM CCS 2026! We propose an RL-based framework that crafts short, natural-language prompts to trap LRMs into pathologically long reasoning, with a constant-time surrogate reward enabling 4.39×10⁵× training speedup. Just 10% malicious traffic cuts benign throughput by 49.8% and monopolizes 64.3% of compute. Check out our paper, website, code, and dataset. |
| Feb 2026 | ReasoningBomb is now on arXiv. Check out our website, code, and dataset. |
| Sep 2024 | Passed my Qualifying Exam. |