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NeurIPS 2026Scale AIU Minnesota, MinneapolisLLM agents & planning

Wayfinder: Adaptive Resource Routing from Agent Citations

Miguel Romero Calvo, George Karypis

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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0/20 AI panelreviewers recommend it

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AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
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NeurIPS 2026North Carolina StatePennsylvania StateScale AISnapchatGraph neural networks

IncAgg: Efficient Memory-Enhanced Graph Learning via Incremental Aggregation

Xingyue Shi, Zhichao Hou, Jiahao Zhang, Suhang Wang and 3 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
67%Highly rated
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NeurIPS 2026U Pennsylvania, University of PeCenter for AI SafetyScale AIU Pennsylvania Aethra LabsLLM evaluation & benchmarks

Beyond Truthfulness: Evaluating Honesty in Large Language Models

Richard Ren, Arunim Agarwal, Mantas Mazeika, Cristina Menghini and 11 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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2/20 AI panelreviewers recommend it

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AI panel: 2 of 20 reviewers recommend it
lenient 1/5
medium 1/10
strict 0/5
86%Must read
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NeurIPS 2026U PennsylvaniaScale AIDyna RoboticsU Nevada, Las VegasU ArizonaAgent benchmarks & environments

SWE Atlas: Benchmarking Coding Agents Beyond Issue Resolution

SWE Atlas benchmarks coding agents on codebase Q&A, test writing, and refactoring, finding frontier models lead but all struggle with edge cases and engineering quality.

Mohit Raghavendra, Soham Dan, Miguel Romero Calvo, Yannis He and 11 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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14/20 AI panelreviewers recommend it

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AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 1/5
92%Must read
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NeurIPS 2026NorthwesternScaleAIScale AIReflection AIU California, BerkeleyAgent benchmarks & environments

MCP-Atlas: A Large-Scale Benchmark for Tool-Use Competency with Real MCP Servers

MCP-Atlas benchmarks LLM tool-use on 1,000 real-server tasks, finding frontier models reach 82.2% pass rates but 63.3% of failures are cognitive.

Chaithanya Bandi, Razvan Dumitru, Ben Hertzberg, Divyansh Agarwal and 15 more

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026 · ▲ 1 on Hugging Face

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19/20 AI panelreviewers recommend it

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AI panel: 19 of 20 reviewers recommend it
lenient 5/5
medium 9/10
strict 5/5