Multi-Task vs. Single-Task ICR: Quantifying the High Sensitivity to Distractor Facts in Reasoning Post date October 29, 2025 Post author By The Tech Reckoning is Upon Us! Post categories In contextual-knowledge, fine-tuned-llms, ft-icr, in-context-reasoning, llm, llm-benchmarking, llm-sensitivity, reckoning-algorithm
Meta-Learning for Reasoning: Summary of RECKONING’s Superior Performance and Future Impact Post date October 28, 2025 Post author By The Tech Reckoning is Upon Us! Post categories In algorithms, bi-level-learning, distractor-robustness, in-context-reasoning, knowledge-encoding, llm-generalization, multi-hop-reasoning, reckoning-algorithm
Meta-Learning for Reasoning: Summary of RECKONING’s Superior Performance and Future Impact Post date October 28, 2025 Post author By The Tech Reckoning is Upon Us! Post categories In algorithms, bi-level-learning, distractor-robustness, in-context-reasoning, knowledge-encoding, llm-generalization, multi-hop-reasoning, reckoning-algorithm
Distractor Robustness: RECKONING Significantly Outperforms FT-ICR in Reasoning Over Irrelevant Facts Post date October 24, 2025 Post author By The Tech Reckoning is Upon Us! Post categories In algorithms, distractor-robustness, gpt-2, in-context-reasoning, knowledge-disentanglement, llm-generalization, reasoning, reckoning-algorithm
Generalization and Robustness: RECKONING Excels on Longer Reasoning Chains Unseen During Training Post date October 24, 2025 Post author By The Tech Reckoning is Upon Us! Post categories In algorithms, ft-icr-baseline, gpt-2, in-context-reasoning, knowledge-encoding, model-generalization, multi-hop-reasoning, reckoning-algorithm
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