Bench 2026 - Calls for Papers#
Overview#
The 18th BenchCouncil International Symposium on Evaluation Science and Engineering (Bench 2026) will be held in Guilin, China, on Nov 6-8, 2026.
Bench is an international symposium organized by the International Open Benchmark Council (BenchCouncil), dedicated to advancing Evaluatology (Evaluation Science and Engineering). The symposium promotes systematic, rigorous, reproducible, and scientifically grounded approaches for evaluation across disciplines, with the goal of establishing evaluation as a unified scientific and engineering practice.
Bench 2026 welcomes original research and engineering contributions from a broad range of disciplines, including computer science, artificial intelligence, medicine and healthcare, education, finance and economics, business and management, psychology, earth sciences, social sciences, engineering, and related fields.
The conference particularly encourages interdisciplinary research and practical experiences related to evaluation theory, evaluation methodologies, benchmark construction, dataset development, measurement and testing, evaluation standards, performance analysis, and real-world evaluation practices.
Bench has successfully been held for seventeen editions. Proceedings from previous Bench conferences have been published in Springer Lecture Notes in Computer Science (LNCS) and indexed by EI Compendex.
Previous Bench conference proceedings:
https://link.springer.com/conference/bench
New Submission and Publication Model#
Bench 2026 introduces a new continuous-submission model.
Authors may submit manuscripts throughout the year. All submissions undergo rigorous double-blind peer review through the BenchCouncil submission system.
Papers accepted within the Bench 2026 review cycle will be included in the Bench 2026 technical program after satisfying the conference presentation requirement.
For detailed information about the new submission workflow, publication pathways, PEvaluation, TBench Special Issue, and presentation policy, please refer to:
Submission Guidelines#
Submission Language#
All submissions must be written in English.
Submission Format#
Authors should prepare manuscripts according to the official PEvaluation manuscript template and formatting guidelines.
- Template: Download Here
- Submissions must be uploaded through the BenchCouncil submission system: Submit Here
Review Policy#
Bench 2026 follows a strict double-blind peer-review process. Authors must ensure that submitted manuscripts are fully anonymized. The submitted manuscript must not include:
- Author names
- Affiliations
- Acknowledgments
- Funding information
- Other identifying information
Submission Requirements#
Submitted manuscripts must satisfy the following requirements:
- The manuscript must describe original work that has not been published elsewhere.
- The manuscript must not be under review by another conference, journal, or publication venue at - the time of submission.
- The submitted version must be properly anonymized for double-blind review.
- The manuscript must be submitted as a printable PDF file.
- The manuscript should include page numbers.
- Figures and tables should remain readable when printed in black and white.
- References should provide complete author lists whenever possible and avoid unnecessary use of “et al.”
Submission System#
All submissions should be made through the BenchCouncil Submission System:
https://journal.benchcouncil.org/PEvaluation/submission
Important Dates#
Submission: Continuous submission throughout the year
Acceptance deadline for inclusion in Bench 2026: November 1, 2026 (AoE)
Bench 2026 Conference: November 6–8, 2026
Location: Guilin, China
Topics of Interest#
Bench 2026 invites original research papers, system papers, benchmark papers, dataset papers, measurement papers, industrial experience papers, survey papers, reproducibility papers, and position papers related to Evaluation Science and Engineering.
Topics of interest include, but are not limited to:
- Mathematical modeling and formal specification of evaluation requirements
- Development and evolution of evaluation models
- Evaluation methodology and theoretical foundations
- Design and implementation of evaluation systems
- Evaluation risk modeling and quantitative analysis
- Cost modeling and optimization for evaluations
- Accuracy modeling and error propagation analysis
- Evaluation traceability
- Identification and standardization of evaluation conditions
- Equivalent evaluation conditions and their verification
- Experimental design methodologies
- Statistical analysis techniques for evaluation
- Identification and elimination of confounding factors
- Analytical modeling and model validation
- Simulation and emulation-based modeling and validation
- Domain-specific evaluation methodologies
- Benchmark design and implementation
- Benchmark traceability
- Construction of equivalent evaluation conditions
- Evaluation metric and index system design
- Scale design and standardization
- Evaluation standard design and implementation
- Evaluation tools and toolchains
- Real-world evaluation systems
- Evaluation platforms and testbeds
- Industrial evaluation practices
- Dataset construction and development
- Dataset quality evaluation
- Dataset documentation and metadata standards
- Dataset collection, validation, and verification protocols
- Dataset reproducibility and reuse
- Dataset resampling and meta-analysis techniques
- Large-scale data generation while preserving data characteristics
- Evaluation frameworks for data-generation experiments
- Data sharing infrastructures for reproducible research
- Benchmark design and construction
- Benchmark suites and benchmark ecosystems
- Benchmark validation and maintenance
- Benchmark evolution methodologies
- Leaderboards and ranking systems
- State-of-the-art and state-of-the-practice analysis
- Industrial benchmarking practices
- Real-world application and system evaluation
- Evaluation of emerging technologies in practical scenarios
- Workload characterization
- Instrumentation, sampling, tracing, and profiling
- Measurement methodologies for large-scale systems
- Testing methodologies and frameworks
- Measurement-driven knowledge discovery
- Performance modeling and bottleneck analysis
- Scalability and efficiency evaluation
- Monitoring and visualization of measurement data
- Reproducible measurement practices
- Re-evaluation of previous empirical measurements and conclusions
- Benchmark-driven algorithm evaluation
- Standardized evaluation of algorithms
- Algorithm performance analysis
- Generalization, robustness, fairness, and reliability evaluation
- Hardware-aware algorithm evaluation and co-design
- Accuracy-cost and efficiency-quality trade-off analysis
- Adaptive evaluation under dynamic environments
- Reproducibility of algorithm evaluation
- Optimization driven by evaluation feedback
- Foundation model evaluation
- Large language model evaluation
- AI benchmark development
- Agent evaluation
- Multimodal AI evaluation
- AI safety evaluation
- Robustness evaluation
- Fairness evaluation
- Explainability evaluation
- Human-centered evaluation
- Real-world AI system evaluation
Bench 2026 welcomes evaluation research and engineering practices in, but not limited to:
- Computer science
- Artificial intelligence
- Medicine and healthcare
- Biology
- Education
- Finance and economics
- Business and management
- Psychology
- Social sciences
- Earth sciences
- Environmental sciences
- Transportation
- Energy
- Manufacturing
- Digital humanities
- Other scientific and engineering disciplines
Contact#
For submission-related inquiries, please contact: yangzhengxin@ict.ac.cn