76 citations · 390 across the 60 of their papers we have counts for
6 papers · 1 filter
Correct Answers, Invalid Traces: What Verifiable Grade-School Math Reveals About Chain-of-Thought Traces
Ratish Puduppully, Pranabendu Misra, Paarth Iyer +3
Chain-of-thought traces are widely read as records of how models reach their answers, informing debugging, agent auditing, and claims about reasoning. Testing this interpretation i…
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…
Robust Planning with Compound LLM Architectures: An LLM-Modulo Approach
Atharva Gundawar, Karthik Valmeekam, Mudit Verma +1
Previous work has attempted to boost Large Language Model (LLM) performance on planning and scheduling tasks through a variety of prompt engineering techniques. While these methods…
Learning and Leveraging Verifiers to Improve Planning Capabilities of Pre-trained Language Models
Daman Arora, Subbarao Kambhampati
There have been wide spread claims in the literature about the emergent reasoning capabilities of Pretrained Large Language Models. However, recent studies, have found that their a…
PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change
Karthik Valmeekam, Matthew Marquez, Alberto Olmo +2
Generating plans of action, and reasoning about change have long been considered a core competence of intelligent agents. It is thus no surprise that evaluating the planning and re…