Add code links for all models with replication code available

results/Kairos_10m/config.json

@@ -3,7 +3,7 @@
     "model_type": "zero-shot",
     "model_dtype": "float32",
     "model_link": "https://huggingface.co/mldi-lab/Kairos_10m",
-    "code_link": "https://github.com/foundation-model-research/Kairos",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/kairos.ipynb",
     "org": "ShanghaiTech University",
     "testdata_leakage": "No",
     "replication_code_available": "Yes"

results/Kairos_23m/config.json

@@ -3,7 +3,7 @@
     "model_type": "zero-shot",
     "model_dtype": "float32",
     "model_link": "https://huggingface.co/mldi-lab/Kairos_23m",
-    "code_link": "https://github.com/foundation-model-research/Kairos",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/kairos.ipynb",
     "org": "ShanghaiTech University",
     "testdata_leakage": "No",
     "replication_code_available": "Yes"

results/Kairos_50m/config.json

@@ -3,7 +3,7 @@
     "model_type": "zero-shot",
     "model_dtype": "float32",
     "model_link": "https://huggingface.co/mldi-lab/Kairos_50m",
-    "code_link": "https://github.com/foundation-model-research/Kairos",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/kairos.ipynb",
     "org": "ShanghaiTech University",
     "testdata_leakage": "No",
     "replication_code_available": "Yes"

results/Lag-Llama/config.json

@@ -5,5 +5,5 @@
     "model_link": "https://huggingface.co/time-series-foundation-models/Lag-Llama",
     "org": "Morgan Stanley & Service Now",
     "testdata_leakage": "Yes",
-    "replication_code_available": "Yes"
+    "replication_code_available": "No"
 }

results/Moirai2/config.json

@@ -3,7 +3,7 @@
     "model_type": "pretrained",
     "model_dtype": "float32",
     "model_link": "https://huggingface.co/Salesforce/moirai-2.0-R-small",
-    "code_link": "https://github.com/SalesforceAIResearch/uni2ts",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/moirai2.ipynb",
     "org": "Salesforce AI Research",
     "testdata_leakage": "No",
     "replication_code_available": "Yes"

results/TTM-R1-Pretrained/config.json

@@ -3,6 +3,7 @@
     "model_type": "pretrained",
     "model_dtype": "float32",
     "model_link": "https://huggingface.co/ibm-granite/granite-timeseries-ttm-r1",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/ttm.ipynb",
     "org": "IBM Research",
     "testdata_leakage": "Yes",
     "replication_code_available": "Yes"

results/TTM-R2-Pretrained/config.json

@@ -3,6 +3,7 @@
     "model_type": "pretrained",
     "model_dtype": "float32",
     "model_link": "https://huggingface.co/ibm-granite/granite-timeseries-ttm-r2",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/ttm.ipynb",
     "org": "IBM Research",
     "testdata_leakage": "Yes",
     "replication_code_available": "Yes"

results/TiRex/config.json

@@ -3,6 +3,7 @@
     "model_type": "zero-shot",
     "model_dtype": "float32",
     "model_link": "https://huggingface.co/NX-AI/TiRex-1.1-gifteval",
+    "code_link":"https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/tirex.ipynb",
     "org": "NXAI",
     "testdata_leakage": "No",
     "replication_code_available": "Yes"

results/TimeCopilot/config.json

@@ -3,6 +3,7 @@
     "model_type": "agentic",
     "model_dtype": "float32",
     "model_link": "https://github.com/AzulGarza/TimeCopilot",
+    "code_link": "https://github.com/AzulGarza/timecopilot/tree/main/experiments/gift-eval",
     "testdata_leakage": "No",
     "replication_code_available": "Yes"
 }

results/Toto_Open_Base_1.0/config.json

@@ -3,6 +3,7 @@
     "model_type": "zero-shot",
     "model_dtype": "float32",
     "model_link": "https://huggingface.co/Datadog/Toto-Open-Base-1.0",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/toto.ipynb",
     "org": "Datadog",
     "testdata_leakage": "No",
     "replication_code_available": "Yes"

results/YingLong_110m/config.json

@@ -3,6 +3,7 @@
     "model_type": "zero-shot",
     "model_dtype": "bf16",
     "model_link": "https://huggingface.co/qcw2333/YingLong_110m",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/yinglong.ipynb",
     "org": "Alibaba",
     "testdata_leakage": "No",
     "replication_code_available": "Yes"

results/YingLong_300m/config.json

@@ -3,6 +3,7 @@
     "model_type": "zero-shot",
     "model_dtype": "bf16",
     "model_link": "https://huggingface.co/qcw2333/YingLong_300m",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/yinglong.ipynb",
     "org": "Alibaba",
     "testdata_leakage": "No",
     "replication_code_available": "Yes"

results/YingLong_50m/config.json

@@ -3,6 +3,7 @@
     "model_type": "zero-shot",
     "model_dtype": "bf16",
     "model_link": "https://huggingface.co/qcw2333/YingLong_50m",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/yinglong.ipynb",
     "org": "Alibaba",
     "testdata_leakage": "No",
     "replication_code_available": "Yes"

results/YingLong_6m/config.json

@@ -3,6 +3,7 @@
     "model_type": "zero-shot",
     "model_dtype": "bf16",
     "model_link": "https://huggingface.co/qcw2333/YingLong_6m",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/yinglong.ipynb",
     "org": "Alibaba",
     "testdata_leakage": "No",
     "replication_code_available": "Yes"

results/naive/config.json

@@ -3,5 +3,7 @@
     "model_type": "statistical",
     "model_dtype": "float32",
     "testdata_leakage": "No",
+    "model_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/naive.ipynb",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/naive.ipynb",
     "replication_code_available": "Yes"
 }

results/seasonal_naive/config.json

@@ -2,6 +2,8 @@
     "model": "Seasonal_Naive",
     "model_type": "statistical",
     "model_dtype": "float32",
+    "model_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/naive.ipynb",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/naive.ipynb",
     "testdata_leakage": "No",
     "replication_code_available": "Yes"
 }

results/sundial_base_128m/config.json

@@ -3,6 +3,7 @@
     "model_type": "zero-shot",
     "model_dtype": "float32",
     "model_link": "https://huggingface.co/thuml/sundial-base-128m",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/sundial.ipynb",
     "org": "Tsinghua University",
     "testdata_leakage": "No",
     "replication_code_available": "Yes"

results/tabpfn_ts/config.json

@@ -3,6 +3,7 @@
     "model_type": "zero-shot",
     "model_dtype": "float32",
     "model_link": "https://github.com/liam-sbhoo/tabpfn-time-series/tree/main",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/tabpfn_ts.ipynb",
     "org": "PriorLabs",
     "testdata_leakage": "No",
     "replication_code_available": "Yes"

results/timesfm/config.json

@@ -3,6 +3,7 @@
     "model_type": "pretrained",
     "model_dtype": "float32",
     "model_link": "https://huggingface.co/google/timesfm-1.0-200m",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/timesfm.ipynb",
     "org": "Google Research",
     "testdata_leakage": "Yes",
     "replication_code_available": "Yes"

results/visionts/config.json

@@ -5,5 +5,5 @@
     "model_link": "https://github.com/Keytoyze/VisionTS",
     "org": "Zhejiang University",
     "testdata_leakage": "No",
-    "replication_code_available": "Yes"
+    "replication_code_available": "No"
 }

src/about.py

@@ -45,7 +45,7 @@ LLM_BENCHMARKS_TEXT = f"""
 ## Update Log
 
 ### 2025-10-17
-- Added new column: Replication Code to indicate whether the model's evaluation code is made available. This column is a binary indicator specifying whether the model's evaluation code is made available to the public by the submission author. The preferable way to share the evaluation code is to share a notebook in the GIFT-Eval github repository (as many previous submissions have done), but a standalone repo for the evaluation code is also acceptable as long as it is accessible to the public and the link is provided in the config.json file.
+- Added new column: Replication Code to indicate whether the model' evaluation replication code is made available. This column is a binary indicator specifying whether the evaluation code is made available to the public by the submission author. The preferable way to share the evaluation code is to share a notebook in the GIFT-Eval github repository (as many previous submissions have done), but a standalone repo for the evaluation code is also acceptable as long as it is accessible to the public and the link is provided in the config.json file through the `code_link` field.
 
 ### 2025-08-25
 - Added new model type: Zero-shot to distinguish between foundation model submissions that don't use training data of GIFT-Eval. Now models tagged with zero-shot indicate that the model is not trained on the GIFT-Eval training data. Test data leakage is still separately tracked with the TestData Leakage column. For a model be tagged as `zero-shot`, it must both not have test data leakage and not use any training split from GIFT-Eval.