# SSum

Source: [SSum](<https://www.sota2.com/research/dataset/ssum>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Benchmarks

Page 1 of 1. This is an index page, not the full collection.

- [Positive-Unlabeled Classification on 14 imbalanced datasets SCAR assumption macro-averaged](<https://www.sota2.com/research/sota/positive-unlabeled-classification-on-14-imbalanced-datasets-scar-assumption-macro-averaged.md>): Positive-Unlabeled Classification; 14 imbalanced datasets SCAR assumption macro-averaged.

- [Factual Consistency Evaluation on SSum](<https://www.sota2.com/research/sota/factual-consistency-evaluation-on-ssum.md>): Factual Consistency Evaluation; SSum.

- [Summarization on CrossSum 1.0 (test)](<https://www.sota2.com/research/sota/summarization-on-crosssum-1-0-test.md>): Summarization; CrossSum 1.0 (test).

- [Long-form Answer Generation on NewsSumm](<https://www.sota2.com/research/sota/long-form-answer-generation-on-newssumm.md>): Long-form Answer Generation; NewsSumm.

- [Epsilon-stationary point finding on Non-convex Stochastic Optimization Average Smoothness Assumption](<https://www.sota2.com/research/sota/epsilon-stationary-point-finding-on-non-convex-stochastic-optimization-average-smoothness-assumption.md>): Epsilon-stationary point finding; Non-convex Stochastic Optimization Average Smoothness Assumption.

- [Epsilon-stationary point finding on Non-convex Stochastic Optimization (Individual Smoothness Assumption)](<https://www.sota2.com/research/sota/epsilon-stationary-point-finding-on-non-convex-stochastic-optimization-individual-smoothness-assumption.md>): Epsilon-stationary point finding; Non-convex Stochastic Optimization Individual Smoothness Assumption.

- [Cross-Lingual Summarization on CrossSum](<https://www.sota2.com/research/sota/cross-lingual-summarization-on-crosssum.md>): Cross-Lingual Summarization; CrossSum.

- [Graph Completion on NVD Open-world assumption (August 2021 to November 2021)](<https://www.sota2.com/research/sota/graph-completion-on-nvd-open-world-assumption-august-2021-to-november-2021.md>): Graph completion; NVD Open-world assumption (August 2021 to November 2021).

- [Cross-lingual Summarization on CrossSum (test-dev)](<https://www.sota2.com/research/sota/cross-lingual-summarization-on-crosssum-test-dev.md>): Cross-lingual summarization; CrossSum (test-dev).

- [Matrix Factorization Optimization on Optimization Problem Local Assumptions](<https://www.sota2.com/research/sota/matrix-factorization-optimization-on-optimization-problem-local-assumptions.md>): Matrix Factorization Optimization; Optimization Problem Local Assumptions.

- [Online fulfillment on Single-FDC K = 1 Assumption 2 (Time-invariant)](<https://www.sota2.com/research/sota/online-fulfillment-on-single-fdc-k-1-assumption-2-time-invariant.md>): Online fulfillment; Single-FDC K = 1 Assumption 2 (Time-invariant).

- [Private estimation on Monotone functions satisfying Assumption 1.1](<https://www.sota2.com/research/sota/private-estimation-on-monotone-functions-satisfying-assumption-1-1.md>): Private estimation; Monotone functions satisfying Assumption 1.1.

- [Online fulfillment on Single-FDC K = 1 Assumption 1 (Time-varying)](<https://www.sota2.com/research/sota/online-fulfillment-on-single-fdc-k-1-assumption-1-time-varying.md>): Online fulfillment; Single-FDC K = 1 Assumption 1 (Time-varying).

- [Online fulfillment on Multi-FDC (K ≥ 2) Assumption 2 (Time-invariant)](<https://www.sota2.com/research/sota/online-fulfillment-on-multi-fdc-k-2-assumption-2-time-invariant.md>): Online fulfillment; Multi-FDC (K ≥ 2) Assumption 2 (Time-invariant).

- [Online fulfillment on Multi-FDC (K ≥ 2) Assumption 1 (Time-varying)](<https://www.sota2.com/research/sota/online-fulfillment-on-multi-fdc-k-2-assumption-1-time-varying.md>): Online fulfillment; Multi-FDC (K ≥ 2) Assumption 1 (Time-varying).

- [Efficient Estimation from Samples Truncated to Unknown Survival Set on Log-concave exponential family satisfying Assumption 4](<https://www.sota2.com/research/sota/efficient-estimation-from-samples-truncated-to-unknown-survival-set-on-log-concave-exponential-family-satisfying-assumption-4.md>): Efficient Estimation from Samples Truncated to Unknown Survival Set; Log-concave exponential family satisfying Assumption 4.

- [Stochastic Optimization on Stochastic function value oracle Assumption 2](<https://www.sota2.com/research/sota/stochastic-optimization-on-stochastic-function-value-oracle-assumption-2.md>): Stochastic Optimization; Stochastic function value oracle Assumption 2.

- [Variational Inference on Strongly Convex Assumptions](<https://www.sota2.com/research/sota/variational-inference-on-strongly-convex-assumptions.md>): Variational Inference; Variational Inference Strongly convex assumptions.

- [Variational Inference Convex assumptions](<https://www.sota2.com/research/sota/variational-inference-convex-assumptions.md>): Variational Inference; Variational Inference Convex assumptions.

- [Variational Inference General assumptions](<https://www.sota2.com/research/sota/variational-inference-general-assumptions.md>): Variational Inference; Variational Inference General assumptions.

- [Finding an epsilon-optimal policy on Simulator Model with Stochastic Transitions Completeness assumption](<https://www.sota2.com/research/sota/finding-an-epsilon-optimal-policy-on-simulator-model-with-stochastic-transitions-completeness-assumption.md>): Finding an epsilon-optimal policy; Simulator Model with Stochastic Transitions Completeness assumption.

- [Finding an epsilon-optimal policy on Simulator Model Gap Condition (Realizability assumption)](<https://www.sota2.com/research/sota/finding-an-epsilon-optimal-policy-on-simulator-model-gap-condition-realizability-assumption.md>): Finding an epsilon-optimal policy; Simulator Model Gap Condition (Realizability assumption).

- [Finding an epsilon-optimal policy on Online RL with Deterministic Transitions Realizability assumption](<https://www.sota2.com/research/sota/finding-an-epsilon-optimal-policy-on-online-rl-with-deterministic-transitions-realizability-assumption.md>): Finding an epsilon-optimal policy; Online RL with Deterministic Transitions Realizability assumption.

- [Finding an epsilon-optimal policy on Simulator Model Deterministic Transitions (Realizability assumption)](<https://www.sota2.com/research/sota/finding-an-epsilon-optimal-policy-on-simulator-model-deterministic-transitions-realizability-assumption.md>): Finding an epsilon-optimal policy; Simulator Model Deterministic Transitions (Realizability assumption).