activity
20242026
collaborators

15 papers

cs.LG2026

Test-Time Scaling in Reasoning LLMs: Inference Regimes, Evaluation, and Reproducibility

Mohsen Hariri, Weicong Chen, Nahal Shahini +11

Large language models can solve substantially harder reasoning problems with more inference-time compute. The term "test-time scaling," however, now covers diverse inference algori…

cs.CL2026

Mid-Think: Training-Free Intermediate-Budget Reasoning via Token-Level Triggers

Wang Yang, Debargha Ganguly, Xinpeng Li +5

Hybrid reasoning language models are commonly controlled through high-level Think/No-think instructions to regulate reasoning behavior, yet we found that such mode switching is lar…

cs.LG2026

Privacy Policy Enforcement Guardrails for Data-Sensitive Retrieval-Augmented Generation

Osama Zafar, Alexander Nemecek, Yiqian Zhang +5

Standard PII filters often miss contextual data leakage in RAG systems, such as non-regulated attribute clusters that collectively identify individuals. We introduce a Privacy Poli…

cs.LG2026

CausalGuard: Conformal Inference under Graph Uncertainty

Vikash Singh, Weicong Chen, Debargha Ganguly +12

Estimating treatment effects from observational data requires choosing an adjustment set, but valid adjustment depends on an unknown causal graph. Graph misspecification can cause…

cs.LG2026

Reliability-Gated Source Anchoring for Continual Test-Time Adaptation

Vikash Singh, Debargha Ganguly, Weicong Chen +8

Continual test-time adaptation (CTTA) updates a pretrained model online on an unlabeled, non-stationary stream while anchoring it to a frozen source checkpoint. This anchor is usef…

cs.CL2026

Path-Lock Expert: Separating Reasoning Mode in Hybrid Thinking via Architecture-Level Separation

Shouren Wang, Wang Yang, Chuang Ma +7

Hybrid-thinking language models expose explicit /think and /no_think modes, but current designs do not separate them cleanly. Even in /no_think mode, models often emit long and sel…