23 citations · 79 across the 17 of their papers we have counts for
5 papers · 1 filter
Local Coherence or Global Validity? Investigating RLVR Traces in Math Domains
Soumya Rani Samineni, Durgesh Kalwar, Vardaan Gangal +2
Reinforcement Learning with Verifiable Rewards (RLVR)-based post-training of Large Language Models (LLMs) has been shown to improve accuracy on reasoning tasks and continues to att…
Do Cognitively Interpretable Reasoning Traces Improve LLM Performance?
Siddhant Bhambri, Upasana Biswas, Subbarao Kambhampati
Recent progress in reasoning-oriented Large Language Models (LLMs) has been driven by introducing Chain-of-Thought (CoT) traces, where models generate intermediate reasoning traces…
Interpretable Traces, Unexpected Outcomes: Investigating the Disconnect in Trace-Based Knowledge Distillation
Siddhant Bhambri, Upasana Biswas, Subbarao Kambhampati
Recent advances in reasoning-focused Large Language Models (LLMs) have introduced Chain-of-Thought (CoT) traces - intermediate reasoning steps generated before a final answer. Thes…
Position: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces!
Subbarao Kambhampati, Karthik Valmeekam, Siddhant Bhambri +6
Intermediate token generation (ITG), where a model produces output before the solution, has become a standard method to improve the performance of language models on reasoning task…
Who is Helping Whom? Analyzing Inter-dependencies to Evaluate Cooperation in Human-AI Teaming
Upasana Biswas, Vardhan Palod, Siddhant Bhambri +1
State-of-the-art methods for Human-AI Teaming and Zero-shot Cooperation focus on task completion, i.e., task rewards, as the sole evaluation metric while being agnostic to how the…