Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems | Paper Citation Record

Observation b0668d78-5cb6-4e6c-a4aa-98c51df35f78 · outbound

This paper cites Graph of thoughts: Solving elaborate problems with large language models.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Graph of thoughts: Solving elaborate problems with large language models

Reference 1

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Observation 05c6b53f-e4b1-4663-8a3c-4b0b0325e661 · outbound

This paper cites O’Reilly Media, Inc., 2009.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems O’Reilly Media, Inc., 2009

Reference 2

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Observation ecfd69c8-3522-4618-90d1-e160bf81084c · outbound

This paper cites Springer, 2006.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Springer, 2006

Reference 3

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Observation 413de852-5dd9-4b3e-944c-186b657c1681 · outbound

This paper cites Grounding large language models in interactive environments with online reinforcement learning.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Grounding large language models in interactive environments with online reinforcement learning

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This paper cites Agentboard: An analytical evaluation board of multi-turn llm agents.Advances in neural information processing systems, 37:74325–74362, 2024.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Agentboard: An analytical evaluation board of multi-turn llm agents.Advances in neural information processing systems, 37:74325–74362, 2024

Reference 5

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Observation b35807e4-fae5-419d-a086-825e7bb85ae3 · outbound

This paper cites FireAct: Toward Language Agent Fine-tuning.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems FireAct: Toward Language Agent Fine-tuning

Reference 6

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Observation c529326f-0192-4fc6-b058-0c044d128190 · outbound

This paper cites RoboGPT: an intelligent agent of making embodied long-term decisions for daily instruction tasks.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems RoboGPT: an intelligent agent of making embodied long-term decisions for daily instruction tasks

Reference 7

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Observation 64606010-e5de-44e6-809b-3556882f7cb9 · outbound

This paper cites TextWorld: A Learning Environment for Text-based Games.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems TextWorld: A Learning Environment for Text-based Games

Reference 8

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Observation 996a1a99-765f-409c-87c1-fb249199968a · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Bert: Pre-training of deep bidirectional transformers for language understanding

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Observation 0357104b-5b14-4e46-ab71-87fc5a8c289d · outbound

This paper cites Retrieval augmented language model pre-training.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Retrieval augmented language model pre-training

Reference 10

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Observation b72044fc-8636-43c2-86e9-d31431f133aa · outbound

This paper cites Reasoning with Language Model is Planning with World Model.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Reasoning with Language Model is Planning with World Model

Reference 11

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Observation f4d5b2fd-3a89-432b-aadc-0f5356039c75 · outbound

This paper cites Goucher, Adam Perelman, Aditya Ramesh, Aidan Clark, AJ Ostrow, Akila Welihinda, et al.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Goucher, Adam Perelman, Aditya Ramesh, Aidan Clark, AJ Ostrow, Akila Welihinda, et al

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Observation ae571369-7a89-4cae-80ea-7c19a657f653 · outbound

This paper cites MapCoder: Multi-Agent Code Generation for Competitive Problem Solving.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems MapCoder: Multi-Agent Code Generation for Competitive Problem Solving

Reference 13

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Observation eb4a9f3d-bf21-463e-8651-d8e83dbc14c9 · outbound

This paper cites Jansen and Marc-Alexandre Côté.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Jansen and Marc-Alexandre Côté

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Observation a93c2c59-dcb5-45a9-a050-6d73cfd45cae · outbound

This paper cites RAP: Retrieval-Augmented Planning with Contextual Memory for Multimodal LLM Agents.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems RAP: Retrieval-Augmented Planning with Contextual Memory for Multimodal LLM Agents

Reference 15

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Observation 06427f5b-ab11-40c2-85cc-fd8b9ab60d28 · outbound

This paper cites Kipf and Max Welling.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Kipf and Max Welling

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Observation 2023338c-0bbf-413e-ac03-767e990214c7 · outbound

This paper cites The MIT Press, 2009.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems The MIT Press, 2009

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Observation b800f9e0-ecca-4469-a666-dbb90158c4c2 · outbound

This paper cites Complex knowledge base question answering: A survey.IEEE Transactions on Knowledge and Data Engineering, 35(11):11196–11215, 2022.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Complex knowledge base question answering: A survey.IEEE Transactions on Knowledge and Data Engineering, 35(11):11196–11215, 2022

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Observation 1e0c512d-58a2-4437-a252-e7577ab94059 · outbound

This paper cites Dhrl: A graph-based approach for long-horizon and sparse hierarchical reinforcement learning.Advances in Neural Information Processing Systems, 35:13668–13678, 2022.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Dhrl: A graph-based approach for long-horizon and sparse hierarchical reinforcement learning.Advances in Neural Information Processing Systems, 35:13668–13678, 2022

Reference 19

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Observation f76233e0-73dc-43ce-97c6-402607d36700 · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive nlp tasks.Advances in neural information processing systems, 33:9459–9474, 2020.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Retrieval-augmented generation for knowledge-intensive nlp tasks.Advances in neural information processing systems, 33:9459–9474, 2020

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Observation 12f80f25-cfe8-4e07-831c-78ad0d3957b8 · outbound

This paper cites Decoding on Graphs: Faithful and Sound Reasoning on Knowledge Graphs through Generation of Well-Formed Chains.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Decoding on Graphs: Faithful and Sound Reasoning on Knowledge Graphs through Generation of Well-Formed Chains

Reference 21

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Observation 21a6ad3e-4eef-4ca3-bcc6-800cbc4ab567 · outbound

This paper cites Embodied agent interface: Benchmarking llms for embodied decision making.Advances in Neural Information Processing Systems, 37:100428–100534, 2024.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Embodied agent interface: Benchmarking llms for embodied decision making.Advances in Neural Information Processing Systems, 37:100428–100534, 2024

Reference 22

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Observation 441edc4a-2a98-4a3c-a2e9-c39e631f6040 · outbound

This paper cites A survey on text classification: From traditional to deep learning.ACM Transactions on Intelligent Systems and Technology (TIST), 13(2):1–41, 2022.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems A survey on text classification: From traditional to deep learning.ACM Transactions on Intelligent Systems and Technology (TIST), 13(2):1–41, 2022

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Observation 397a35ce-c551-4d3a-8184-9b6e7ee7b276 · outbound

This paper cites Pre-trained language models for interactive decision-making.Advances in Neural Information Processing Systems, 35:31199–31212, 2022.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Pre-trained language models for interactive decision-making.Advances in Neural Information Processing Systems, 35:31199–31212, 2022

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Observation e2975ba7-78c0-4549-8010-83250ce94396 · outbound

This paper cites Injecting structured knowledge into llms via graph neural networks.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Injecting structured knowledge into llms via graph neural networks

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Observation e5b3ea18-45d5-4fe8-9f64-e6632250e98b · outbound

This paper cites Prompt compression with context-aware sentence encoding for fast and improved llm inference.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Prompt compression with context-aware sentence encoding for fast and improved llm inference

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Observation e4097d5f-0d7a-4c77-a0b7-aa503c122e6f · outbound

This paper cites Fairness and bias in robot learning.Proceedings of the IEEE, 112(4):305–330, 2024.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Fairness and bias in robot learning.Proceedings of the IEEE, 112(4):305–330, 2024

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Observation f54f555c-b183-4d02-9f5f-75def80e868d · outbound

This paper cites Decoupled weight decay regularization.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Decoupled weight decay regularization

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Observation ebe0af0c-e496-4d16-be25-08b991c10c08 · outbound

This paper cites Graph-constrained Reasoning: Faithful Reasoning on Knowledge Graphs with Large Language Models.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Graph-constrained Reasoning: Faithful Reasoning on Knowledge Graphs with Large Language Models

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Observation 362b3043-2009-4ee6-9104-28427bfe0db0 · outbound

This paper cites A Survey on Vision-Language-Action Models for Embodied AI.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems A Survey on Vision-Language-Action Models for Embodied AI

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Observation 1ad1fd9e-fbd3-40b9-a951-1f163e3aa955 · outbound

This paper cites Gnn-rag: Graph neural retrieval for efficient large lan- guage model reasoning on knowledge graphs.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Gnn-rag: Graph neural retrieval for efficient large lan- guage model reasoning on knowledge graphs

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Observation c6f3e680-c8a7-4e07-a029-707485755d8d · outbound

This paper cites Large dual encoders are generalizable retrievers.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Large dual encoders are generalizable retrievers

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Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Unresolved cited work

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Observation a90a5198-0975-49aa-9598-5437ea057622 · outbound

This paper cites Gpt-4o mini: advancing cost-efficient intelligence.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Gpt-4o mini: advancing cost-efficient intelligence

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Observation 2c0f5780-a1bf-448a-9849-2a1d55c5a2c7 · outbound

This paper cites Graphical models for probabilistic and causal reasoning.Quantified representation of uncertainty and imprecision, pages 367–389, 1998.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Graphical models for probabilistic and causal reasoning.Quantified representation of uncertainty and imprecision, pages 367–389, 1998

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Observation 14c6829d-3bf1-4840-99d0-98c22751c374 · outbound

This paper cites Graph Retrieval-Augmented Generation: A Survey.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Graph Retrieval-Augmented Generation: A Survey

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Observation a1069f18-4ccd-4bf0-8042-293fb1d2c909 · outbound

This paper cites Virtualhome: Simulating household activities via programs.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Virtualhome: Simulating household activities via programs

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Observation 379b6f61-1a54-4ad1-8679-7c1197acab34 · outbound

This paper cites ChatDev: Communicative Agents for Software Development.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems ChatDev: Communicative Agents for Software Development

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Observation 83849795-05d8-4bd9-b040-6ab1e573e8b1 · outbound

This paper cites Term-weighting approaches in automatic text retrieval.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Term-weighting approaches in automatic text retrieval

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Observation d84b7e9f-a466-4655-b4bb-bcf42e1e86d8 · outbound

This paper cites Reflex- ion: language agents with verbal reinforcement learning.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Reflex- ion: language agents with verbal reinforcement learning

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Observation bb1eea3d-1103-4289-a388-9e7467a667f2 · outbound

This paper cites ALFWorld: Aligning Text and Embodied Environments for Interactive Learning.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems ALFWorld: Aligning Text and Embodied Environments for Interactive Learning

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Observation e4d25527-dbe6-4bf0-8e64-2cf2c4db6b9d · outbound

This paper cites Trial and Error: Exploration-Based Trajectory Optimization for LLM Agents.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Trial and Error: Exploration-Based Trajectory Optimization for LLM Agents

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Observation dd93d7e7-97a0-499f-8716-0f5a8c9347a0 · outbound

This paper cites MIT press Cambridge, 1998.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems MIT press Cambridge, 1998

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Observation 62d181f2-d668-4032-8b09-a79f62d84232 · outbound

This paper cites A comprehensive survey of text classification techniques and their research applications: Observational and experimental insights.Computer Science Review, 54:100664, 2024.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems A comprehensive survey of text classification techniques and their research applications: Observational and experimental insights.Computer Science Review, 54:100664, 2024

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Observation faf3d9dd-6420-4788-9c5d-74c0159b9c7c · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

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Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Gemma 3 Technical Report

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Observation 198c3575-9dca-4b02-a0d0-8b0670890d39 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems LLaMA: Open and Efficient Foundation Language Models

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Observation c7515389-6d79-4d95-953e-103f9406dcfe · outbound

This paper cites E2CL: Exploration-based Error Correction Learning for Embodied Agents.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems E2CL: Exploration-based Error Correction Learning for Embodied Agents

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Observation a924f989-8c55-44ad-9583-168f12eb114c · outbound

This paper cites STeCa: Step-level Trajectory Calibration for LLM Agent Learning.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems STeCa: Step-level Trajectory Calibration for LLM Agent Learning

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Observation 0fb0980f-8756-484c-be89-a9d1164bb62b · outbound

This paper cites Text Embeddings by Weakly-Supervised Contrastive Pre-training.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Text Embeddings by Weakly-Supervised Contrastive Pre-training

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Observation 39dd211c-7a67-42de-993a-d201c6d70c14 · outbound

This paper cites Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations

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Observation b6e12af4-9680-4d60-9c3d-8c99e48b915d · outbound

This paper cites ScienceWorld: Is your Agent Smarter than a 5th Grader?.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems ScienceWorld: Is your Agent Smarter than a 5th Grader?

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Observation efeb57d2-825c-4f96-9eb5-3fc3347418b3 · outbound

This paper cites MiniLMv2: Multi-head self-attention relation distillation for compressing pretrained transformers.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems MiniLMv2: Multi-head self-attention relation distillation for compressing pretrained transformers

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Observation eb4f0de5-af4f-47ae-b31d-6820e173981a · outbound

This paper cites Understanding Reasoning Ability of Language Models From the Perspective of Reasoning Paths Aggregation.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Understanding Reasoning Ability of Language Models From the Perspective of Reasoning Paths Aggregation

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Observation 5476e0eb-a76f-4988-98e1-6bd30cc04fbc · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Self-Consistency Improves Chain of Thought Reasoning in Language Models

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Observation a4bb834f-72b7-4f23-8a04-6aedd4c845bc · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Chain-of-thought prompting elicits reasoning in large language models

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.378019Z

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Observation e26d29ad-2c09-49c0-a456-938a9ebea219 · outbound

This paper cites Autogen: Enabling next-gen llm applications via multi-agent conversations.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Autogen: Enabling next-gen llm applications via multi-agent conversations

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.447926Z

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Observation f2c914c4-e37f-446b-946b-6629870f81f7 · outbound

This paper cites Can graph learning improve planning in llm-based agents?Advances in Neural Information Processing Systems, 37:5338–5383, 2024.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Can graph learning improve planning in llm-based agents?Advances in Neural Information Processing Systems, 37:5338–5383, 2024

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.512365Z

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Observation 16f27dd2-8127-4bc5-a133-56baf189bbc7 · outbound

This paper cites The rise and potential of large language model based agents: A survey.Science China Information Sciences, 68(2):121101, 2025.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems The rise and potential of large language model based agents: A survey.Science China Information Sciences, 68(2):121101, 2025

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.624226Z

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Observation 4411d582-b2d6-4b25-ad03-bcf70f136094 · outbound

This paper cites Language models meet world models: Embodied experiences enhance language models.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Language models meet world models: Embodied experiences enhance language models

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.740404Z

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Observation f7a00d24-7517-4223-8cce-5aedcfa5932d · outbound

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Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems O3D: Offline Data-driven Discovery and Distillation for Sequential Decision-Making with Large Language Models

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.832422Z

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Observation aba49d3b-5652-4c67-961c-2f69238a5e98 · outbound

This paper cites Travelplanner: A benchmark for real-world planning with language agents.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Travelplanner: A benchmark for real-world planning with language agents

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.895231Z

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Observation fdc5e345-4185-4a82-943b-3684e0f894a1 · outbound

This paper cites Revealing the Barriers of Language Agents in Planning.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Revealing the Barriers of Language Agents in Planning

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.898284Z

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Observation 4c53a9ff-d3fa-4631-bbf8-a4207098375a · outbound

This paper cites Watch Every Step! LLM Agent Learning via Iterative Step-Level Process Refinement.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Watch Every Step! LLM Agent Learning via Iterative Step-Level Process Refinement

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.901360Z

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Observation 3665d2e0-ee52-44f9-a094-88476ef235f7 · outbound

This paper cites How powerful are graph neural networks? InInternational Conference on Learning Representations, 2019.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems How powerful are graph neural networks? InInternational Conference on Learning Representations, 2019

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.904721Z

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Observation b7bd7473-8618-455d-9ef1-2302b409d8e5 · outbound

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Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Qwen2.5 Technical Report

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.907736Z

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Observation 44386acd-0f27-472c-9eb1-2b18717fd673 · outbound

This paper cites EmbodiedBench: Comprehensive Benchmarking Multi-modal Large Language Models for Vision-Driven Embodied Agents.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems EmbodiedBench: Comprehensive Benchmarking Multi-modal Large Language Models for Vision-Driven Embodied Agents

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.910645Z

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Observation b68f2dd6-f727-4093-9231-c1b15ba9a845 · outbound

This paper cites Gpt4tools: Teaching large language model to use tools via self-instruction.Advances in Neural Information Processing Systems, 36:71995–72007, 2023.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Gpt4tools: Teaching large language model to use tools via self-instruction.Advances in Neural Information Processing Systems, 36:71995–72007, 2023

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.913948Z

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Observation 67f7ee32-913d-4916-9481-fa7b53b66a81 · outbound

This paper cites Graph convolutional networks for text classi- fication.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Graph convolutional networks for text classi- fication

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.916727Z

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Observation 5aa16c1b-2cb5-4efd-81a5-637840668988 · outbound

This paper cites Tree of thoughts: Deliberate problem solving with large language models.Ad- vances in neural information processing systems, 36:11809–11822, 2023.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Tree of thoughts: Deliberate problem solving with large language models.Ad- vances in neural information processing systems, 36:11809–11822, 2023

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.919502Z

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Observation 0698fb16-338c-4d44-bfd3-fd185c82e899 · outbound

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Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems React: Synergizing reasoning and acting in language models

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.922269Z

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Observation 352804f7-c15d-48d0-9169-55fbacc523ba · outbound

This paper cites RnG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems RnG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.925134Z

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Observation 73c0d025-43c6-4422-922e-00dc725c5d05 · outbound

This paper cites Agent Lumos: Unified and Modular Training for Open-Source Language Agents.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Agent Lumos: Unified and Modular Training for Open-Source Language Agents

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.928143Z

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Observation d8a465d3-6dde-49d6-9a93-e376c85b6101 · outbound

This paper cites Scene Graph-Guided Proactive Replanning for Failure-Resilient Embodied Agent.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Scene Graph-Guided Proactive Replanning for Failure-Resilient Embodied Agent

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.931605Z

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Observation b173eeee-323c-4da1-baa0-0e874dc85a6f · outbound

This paper cites Agent-R: Training Language Model Agents to Reflect via Iterative Self-Training.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Agent-R: Training Language Model Agents to Reflect via Iterative Self-Training

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.934662Z

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Observation 2f25769c-89fe-4995-bbe0-8e188c083be8 · outbound

This paper cites CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding Challenges.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding Challenges

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.937645Z

Source-reported events for the cited work

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Observation 3402a092-f409-4ccb-90c5-789e4db94f4c · outbound

This paper cites Arl: An adaptive reinforcement learning framework for complex question answering over knowledge base.Information Processing & Management, 59(3):102933, 2022.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Arl: An adaptive reinforcement learning framework for complex question answering over knowledge base.Information Processing & Management, 59(3):102933, 2022

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.940733Z

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Observation 54cd529a-521b-4073-9421-0a04358e3fab · outbound

This paper cites Active example selection for in-context learning.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Active example selection for in-context learning

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.943536Z

Source-reported events for the cited work

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Observation 5dd759d3-d44b-4b8e-b14d-e0015be4f827 · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena.Advances in neural information processing systems, 36:46595–46623, 2023.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Judging llm-as-a-judge with mt-bench and chatbot arena.Advances in neural information processing systems, 36:46595–46623, 2023

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.946354Z

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Observation 21b41681-068e-4d2d-928e-adc7b5f67220 · outbound

This paper cites Trad: Enhancing llm agents with step-wise thought retrieval and aligned decision.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Trad: Enhancing llm agents with step-wise thought retrieval and aligned decision

Reference 80

Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.949178Z

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Observation 36fee646-d7d0-4ca5-9d4d-677314c6f595 · outbound

This paper cites Large language models are human-level prompt engineers.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Large language models are human-level prompt engineers

Reference 81

Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.952062Z

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Observation 0c8e7268-3137-4be7-8ec5-13fe1a5972c3 · outbound

This paper cites ToolChain: Efficient Action Space Navigation in Large Language Models with A Search.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search

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Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.955164Z

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Observation 49799a31-fb02-4422-911c-6ce13d525e06 · outbound

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Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems {task_goal}

Reference 83

Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.959098Z

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Observation 645e7dde-709b-442d-ad81-33602554a9a6 · outbound

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Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Unresolved cited work

Reference 84

Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.961996Z

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Observation a832d0db-0051-48dc-81a8-ec5d9ec0343f · outbound

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Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Unresolved cited work

Reference 85

Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.964934Z

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Observation f2072efe-a08e-47ab-b7ac-dc2a79fefa6d · outbound

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Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems {current_action}

Reference 86

Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.967849Z

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Observation dd48e540-de4b-49fa-9d99-e4f7621631a9 · outbound

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Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Unresolved cited work

Reference 87

Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.970934Z

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Observation 7328a3f9-ab69-4685-a4ad-7c48bd34aefa · outbound

This paper cites an unresolved cited work.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Unresolved cited work

Reference 88

Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.973897Z

Source-reported events for the cited work

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Observation ae76fdb0-68f0-4ac6-bf20-4c6f700c50bf · outbound

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Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems It is not necessary

Reference 89

Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.976617Z

Source-reported events for the cited work

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Observation 74f7c599-3a1d-4643-8ed6-a23d8c43a6eb · outbound

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Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems Unresolved cited work

Reference 90

Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.979560Z

Source-reported events for the cited work

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Observation cee01c91-378b-4dfb-829f-d174ca0b34a6 · outbound

This paper cites For example, the current information does not contain the hotel information, so it is not a good time to make final plan.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems For example, the current information does not contain the hotel information, so it is not a good time to make final plan

Reference 91

Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.982305Z

Source-reported events for the cited work

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Observation 9842080c-2e11-4727-a871-613609e3c0ca · outbound

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Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems No error

Reference 92

Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:12.985114Z

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