Papers with problem-solving processes

3 papers
Advancing Oversight Reasoning across Languages for Audit Sycophantic Behaviour via X-Agent (2025.emnlp-main)

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Challenge: Large language models have demonstrated capabilities that are satisfactory to a wide range of users by adapting to their culture and wisdom.
Approach: They propose an Oversight Reasoning framework that audits human–LLM dialogues, reasons about them, captures sycophancy and corrects the final outputs.
Outcome: The proposed framework detects sycophancy, reduces unwarranted agreement and improves cross-turn consistency across different scenarios and languages.
Working Memory Identifies Reasoning Limits in Language Models (2024.emnlp-main)

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Challenge: Using large language models, we examine the limitations of their cognitive capabilities and their working memory.
Approach: They examine the limitations of large language models from a scaling perspective . they also assess various prompting strategies, revealing their diverse impacts on LLM performance.
Outcome: The proposed models perform poorly on n-back tasks and on prompting strategies.
Tracing Mathematical Proficiency Through Problem-Solving Processes (2026.findings-acl)

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Challenge: Knowledge Tracing (KT) models a learner's evolving knowledge state over time, but lacks the rich information embedded in students' problem-solving processes.
Approach: They propose a framework that uses a teacher-student-teacher pipeline to extract students’ Mathematical Proficiency (MP) as intermediate representation.
Outcome: The proposed framework improves the prediction performance of existing KT methods and provides interpretable explanations by explicitly modeling students’ mathematical proficiency.

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