8 citations · 11 across the 7 of their papers we have counts for
5 papers · 1 filter
LeanPRM: Lean-Grounded Process Supervision for Natural Language Proof Verification
Rodney Lafuente-Mercado, Salman Rahman, Jingyan Shen +3
AI systems now write long and difficult mathematical proofs, and checking their step-by-step validity is becoming a bottleneck. A learned verifier could check proofs cheaply, but t…
Locating Hidden Failures Makes Long-Horizon Agents More Reliable
Salman Rahman, Yubin Kim, Mihir Parmar +15
As AI agents take on long, autonomous tasks, we increasingly oversee rather than perform the work, yet we still judge them almost entirely by whether they finally succeed. An outco…
Understanding Reasoning from Pretraining to Post-Training
Jingyan Shen, Ang Li, Salman Rahman +4
Reinforcement learning (RL) has become central to improving large language models (LLMs) on complex reasoning tasks, yet RL post-training is largely studied in isolation from the p…
When Can LLMs Learn to Reason with Weak Supervision?
Salman Rahman, Jingyan Shen, Anna Mordvina +3
Large language models have achieved significant reasoning improvements through reinforcement learning with verifiable rewards (RLVR). Yet as model capabilities grow, constructing h…
Understanding Disparities in Post Hoc Machine Learning Explanation
Vishwali Mhasawade, Salman Rahman, Zoe Haskell-Craig +1
Previous work has highlighted that existing post-hoc explanation methods exhibit disparities in explanation fidelity (across 'race' and 'gender' as sensitive attributes), and while…