mlsanityData to 14 Oct 2026

ContextGuard: Structured Self-Auditing for Context Learning in Language Models

arXiv 2605.26827 ↗First posted 26 May 2026cs.CL cs.AIcited by 3

On the map: LLM reasoning → Reasoning benchmarks and evaluation

Abstract (arXiv)

Recent benchmarks reveal that despite strong reasoning capabilities, large language models (LLMs) still struggle to faithfully apply complex contextual knowledge. These failures are often not wholesale reasoning collapses: in context-rich tasks, models may follow the central reasoning path while missing peripheral, persistent, or format-sensitive requirements.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning. Builds on 18 of its 24 references that are in the map. First posted on arXiv 26 May 2026.

Builds on

18 of 24 references.

Closest ancestors · 1

Same direction, newest first

  1. 2026CL-bench: A Benchmark for Context Learning3 Feb

Other references · 17

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2022Training language models to follow instructions with human feedbackcited by 15,971
  3. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  4. 2023Self-Refine: Iterative Refinement with Self-Feedbackcited by 3,442
  5. 2023Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflectioncited by 1,839
  6. 2023LongBench: A Bilingual, Multitask Benchmark for Long Context Understandingcited by 1,417
  7. 2024RULER: What's the Real Context Size of Your Long-Context Language Models?cited by 1,346
  8. 2023Large Language Models Cannot Self-Correct Reasoning Yetcited by 1,017
  9. 2023CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquingcited by 783
  10. 2023Adaptive Chameleon or Stubborn Sloth: Revealing the Behavior of Large Language Models in Knowledge Conflictscited by 341
  11. 2024ClashEval: Quantifying the tug-of-war between an LLM's internal prior and external evidencecited by 113
  12. 2025VideoMem: Enhancing Ultra-Long Video Understanding via Adaptive Memory Managementcited by 19
5 more
  1. 2026VISD: Enhancing Video Reasoning via Structured Self-Distillationcited by 10
  2. 2026HiMAC: Hierarchical Macro-Micro Learning for Long-Horizon LLM Agentscited by 9
  3. 2026DGPO: Distribution Guided Policy Optimization for Fine Grained Credit Assignmentcited by 7
  4. 2025VideoCuRL: Video Curriculum Reinforcement Learning with Orthogonal Difficulty Decompositioncited by 3
  5. 2026TIR-Flow: Active Video Search and Reasoning with Frozen VLMscited by 3

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 3.

3 papers.

  1. 2026Inside the Unfair Judge: A Mechanistic Interpretability Account of LLM-as-Judge Biascited by 3
  2. 2026ZeroSplat: Generalized Referring Segmentation in 3D Gaussian Splattingcited by 3
  3. 2026GTA: Graph Theory Agent and Benchmark for Algorithmic Graph Reasoning with LLMscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026ConceptGuard: Benchmarking Context-Sensitive Unlearning in Large Language Models
  2. 2026LongHarness Bench: Stress-Testing Language Model Harnesses for Long-Context Reasoning
  3. 2024Large Language Models Can Self-Improve in Long-context Reasoning
  4. 2025RELIC: Evaluating Complex Reasoning via the Recognition of Languages In-Context
  5. 2026ContextFocus: Activation Steering for Contextual Faithfulness in Large Language Models
  6. 2026ReContext: Recursive Evidence Replay as LLM Harness for Long-Context Reasoning
  7. 2023Taken out of context: On measuring situational awareness in LLMs
  8. 2024Improving Large Language Model (LLM) fidelity through context-aware grounding: A systematic approach to reliability and veracity