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README.md

@@ -24,60 +24,60 @@ Each task directory contains three files:
 | Dataset | Domain | Description | Tasks |
 |---------|--------|-------------|------:|
 | [`1d`](1d/README.md) | Visual Reasoning | 1D-ARC grid transformation tasks (Xu et al., AAAI 2023) | 18 types × 50 instances |
-| [`aids`](aids/README.md) | Molecular / Chemical | Antiviral activity against HIV (Riesen & Bunke, SSPR/SPR 2008) | 1 |
-| [`alzheimer`](alzheimer/README.md) | Molecular / Chemical | Drug design for Alzheimer's disease, source attributed to King et al. 1995 | 4 |
+| [`aids`](aids/README.md) | Molecular | Antiviral activity against HIV (Riesen & Bunke, SSPR/SPR 2008) | 1 |
+| [`alzheimer`](alzheimer/README.md) | Molecular | Drug design for Alzheimer's disease, source attributed to King et al. 1995 | 4 |
 | [`arc1`](arc1/README.md) | Visual Reasoning | Abstraction and Reasoning Corpus (Chollet, arXiv 2019) | 2 |
-| [`biodegradability`](biodegradability/README.md) | Molecular / Chemical | Aerobic aqueous biodegradability prediction (Džeroski et al., Applied AI 1998) | 1 |
+| [`biodegradability`](biodegradability/README.md) | Molecular | Aerobic aqueous biodegradability prediction (Džeroski et al., Applied AI 1998) | 1 |
 | [`bongard`](bongard/README.md) | Visual Reasoning | Visual concept learning in the Bongard style (Nie et al., NeurIPS 2020) | 12 |
-| [`bzr`](bzr/README.md) | Molecular / Chemical | Benzodiazepine receptor binding (Sutherland et al., J. Chem. Inf. 2003) | 1 |
-| [`chebi_1624`](chebi_1624/README.md) | Molecular / Chemical | ChEBI ontology molecular classification (Hastings et al., NAR 2016) | 1808 |
+| [`bzr`](bzr/README.md) | Molecular | Benzodiazepine receptor binding (Sutherland et al., J. Chem. Inf. 2003) | 1 |
+| [`chebi_1624`](chebi_1624/README.md) | Molecular | ChEBI ontology molecular classification (Hastings et al., NAR 2016) | 1808 |
 | [`chess`](chess/README.md) | Games | King-Rook vs King endgame (Michie et al., UCI ML Repository 1994) | 3 |
 | [`chess_tactics`](chess_tactics/README.md) | Games | Tactical theme classification from the Lichess open puzzle database, CC0 | 9 |
 | [`clevr`](clevr/README.md) | Visual Reasoning | Visual reasoning tasks derived from CLEVR (Johnson et al., CVPR 2017) | 130 |
 | [`conceptarc`](conceptarc/README.md) | Visual Reasoning | ConceptARC benchmark (Moskvichev et al., arXiv 2023) | 16 |
 | [`conceptnet`](conceptnet/README.md) | Knowledge Graphs | ConceptNet 5.5 commonsense relation prediction (Speer et al., AAAI 2017) | 10 |
 | [`cora`](cora/README.md) | Graph Structure | Author-field token classification in bibliographic references (McCallum et al., IJCAI 1999) | 1 |
-| [`cox2`](cox2/README.md) | Molecular / Chemical | Cyclooxygenase-2 binding (Sutherland et al., J. Chem. Inf. 2003) | 1 |
-| [`dhfr`](dhfr/README.md) | Molecular / Chemical | Dihydrofolate reductase binding (Sutherland et al., J. Chem. Inf. 2003) | 1 |
+| [`cox2`](cox2/README.md) | Molecular | Cyclooxygenase-2 binding (Sutherland et al., J. Chem. Inf. 2003) | 1 |
+| [`dhfr`](dhfr/README.md) | Molecular | Dihydrofolate reductase binding (Sutherland et al., J. Chem. Inf. 2003) | 1 |
 | [`drugdrug`](drugdrug/README.md) | Graph Structure | Drug-drug interaction prediction (Dhami et al., Smart Health 2018) | 1 |
-| [`ecoli`](ecoli/README.md) | Molecular / Chemical | Structure-activity relationships: E. coli, pyrimidines, triazines (Muggleton et al., ML Workshop 1992) | 3 |
+| [`ecoli`](ecoli/README.md) | Molecular | Structure-activity relationships: E. coli, pyrimidines, triazines (Muggleton et al., ML Workshop 1992) | 3 |
 | [`fb15k`](fb15k/README.md) | Knowledge Graphs | Freebase 15K link prediction (Bordes et al., NeurIPS 2013) | 237 |
 | [`flashfill`](flashfill/README.md) | Program Synthesis | FlashFill Excel string transformations (Gulwani, POPL 2011) | 15 |
 | [`geoi_lp`](geoi_lp/README.md) | Other / Synthetic | GeoILP synthetic rule induction benchmark (Chen et al., ICLR 2025) | 1042 |
 | [`grapheval`](grapheval/README.md) | Graph Structure | LeetCode graph algorithm problems, GraphEval36K benchmark (Wu et al., arXiv 2024) | 40 |
-| [`hepatitis`](hepatitis/README.md) | Molecular / Chemical | Hepatitis subtype classification (Motl & Schulte, arXiv 2015) | 1 |
+| [`hepatitis`](hepatitis/README.md) | Molecular | Hepatitis subtype classification (Motl & Schulte, arXiv 2015) | 1 |
 | [`iggp`](iggp/README.md) | Games | Inductive General Game Playing — 50 diverse games (Cropper et al., Machine Learning 2020) | 340 |
 | [`imdb`](imdb/README.md) | Relational / Social | IMDB movie industry relational learning (Blockeel & De Raedt, AI 1998) | 3 |
 | [`iparc`](iparc/README.md) | Visual Reasoning | ILP-flavoured ARC challenge (Challa et al., ILP 2022) | 6 |
-| [`jr`](jr/README.md) | Visual Reasoning | Joining-rows grid transformation tasks (Rule et al., Nature Communications 2024) | 250 |
+| [`jr`](jr/README.md) | Program Synthesis | List function tasks (Rule et al., Nature Communications 2024) | 250 |
 | [`kandinsky`](kandinsky/README.md) | Visual Reasoning | Kandinsky pattern concept learning (Müller & Holzinger, AI 2021) | 24 |
 | [`kinship`](kinship/README.md) | Relational / Social | Family relationship learning (Hinton, CogSci 1986) | 7 |
 | [`legal2logic`](legal2logic/README.md) | Other / Synthetic | Legal2Proleg statutory rule learning (Xue et al., arXiv 2026) | 18 |
 | [`lpp`](lpp/README.md) | Games | Logic program policies for games (Silver et al., AAAI 2020) | 5 |
 | [`mesh`](mesh/README.md) | Graph Structure | Mesh dataset from the IC London ILP dataset collection | 1 |
 | [`mini-arc`](mini-arc/README.md) | Visual Reasoning | Miniature ARC tasks (Kim et al., NeurIPS Workshop 2022) | 149 |
-| [`mol`](mol/README.md) | Molecular / Chemical | Molecular property prediction, OGB collection (Hu et al., NeurIPS 2020) | 61 |
-| [`mutag`](mutag/README.md) | Molecular / Chemical | Mutagenicity of nitroaromatic compounds (Debnath et al., J. Med. Chem. 1991) | 1 |
+| [`mol`](mol/README.md) | Molecular | Molecular property prediction, OGB collection (Hu et al., NeurIPS 2020) | 61 |
+| [`mutag`](mutag/README.md) | Molecular | Mutagenicity of nitroaromatic compounds (Debnath et al., J. Med. Chem. 1991) | 1 |
 | [`nations`](nations/README.md) | Knowledge Graphs | Political/economic/military relations between 14 countries (Rummel, Sage 1972; Kok & Domingos, ICML 2007) | 55 |
-| [`nci1`](nci1/README.md) | Molecular / Chemical | NCI anti-cancer activity benchmark (Wale et al., KAIS 2008) | 1 |
-| [`nci109`](nci109/README.md) | Molecular / Chemical | NCI anti-cancer activity benchmark, companion to NCI1 (Wale et al., KAIS 2008) | 1 |
-| [`peptides_func`](peptides_func/README.md) | Molecular / Chemical | Peptide functional classification, LRGB (Dwivedi et al., NeurIPS 2022) | 10 |
-| [`protein`](protein/README.md) | Molecular / Chemical | Protein function classification from the IC London ILP dataset collection | 1 |
-| [`PTC`](PTC/README.md) | Molecular / Chemical | Predictive Toxicology Challenge carcinogenicity (Helma et al., Bioinformatics 2001) | 1 |
-| [`qm9`](qm9/README.md) | Molecular / Chemical | Quantum chemistry molecular properties (Ramakrishnan et al., Sci. Data 2014) | 15 |
+| [`nci1`](nci1/README.md) | Molecular | NCI anti-cancer activity benchmark (Wale et al., KAIS 2008) | 1 |
+| [`nci109`](nci109/README.md) | Molecular | NCI anti-cancer activity benchmark, companion to NCI1 (Wale et al., KAIS 2008) | 1 |
+| [`peptides_func`](peptides_func/README.md) | Molecular | Peptide functional classification, LRGB (Dwivedi et al., NeurIPS 2022) | 10 |
+| [`protein`](protein/README.md) | Molecular | Protein function classification from the IC London ILP dataset collection | 1 |
+| [`PTC`](PTC/README.md) | Molecular | Predictive Toxicology Challenge carcinogenicity (Helma et al., Bioinformatics 2001) | 1 |
+| [`qm9`](qm9/README.md) | Molecular | Quantum chemistry molecular properties (Ramakrishnan et al., Sci. Data 2014) | 15 |
 | [`relbench`](relbench/README.md) | Other / Synthetic | RelBench relational database prediction tasks (Robinson et al., arXiv 2024) | 59 |
 | [`satellite`](satellite/README.md) | Graph Structure | Satellite dataset from the IC London ILP dataset collection | 1 |
 | [`stepgame`](stepgame/README.md) | Spatial Reasoning | Multi-step spatial relational reasoning (Shi et al., AAAI 2022) | 9 |
 | [`strings`](strings/README.md) | Program Synthesis | Character-level string transformations (Cropper, IJCAI 2019) | 329 |
-| [`tox21`](tox21/README.md) | Molecular / Chemical | Toxicology across 12 assays, OGB (Hu et al., NeurIPS 2020) | 12 |
-| [`toxicology`](toxicology/README.md) | Molecular / Chemical | Carcinogenicity in rodents, CTU Prague (Helma et al., Bioinformatics 2001) | 1 |
+| [`tox21`](tox21/README.md) | Molecular | Toxicology across 12 assays, OGB (Hu et al., NeurIPS 2020) | 12 |
+| [`toxicology`](toxicology/README.md) | Molecular | Carcinogenicity in rodents, CTU Prague (Helma et al., Bioinformatics 2001) | 1 |
 | [`trains`](trains/README.md) | Games | Trains classification (Larson & Michalski, SIGART 1977) | 4 |
 | [`uwcse`](uwcse/README.md) | Relational / Social | UW-CSE university department `advisedby` prediction (Richardson & Domingos, ML 2006) | 1 |
 | [`wn18rr`](wn18rr/README.md) | Knowledge Graphs | WordNet 18 Reduced Relations link prediction (Dettmers et al., AAAI 2018) | 11 |
 | [`yago3_10`](yago3_10/README.md) | Knowledge Graphs | YAGO3 knowledge graph, 10 high-frequency relations (Mahdisoltani et al., CIDR 2015) | 10 |
-| [`yeast`](yeast/README.md) | Molecular / Chemical | Yeast gene function classification (Struyf et al., ECML 2006) | 1 |
+| [`yeast`](yeast/README.md) | Molecular | Yeast gene function classification (Struyf et al., ECML 2006) | 1 |
 | [`zendo`](zendo/README.md) | Visual Reasoning | Zendo concept learning game (Bramley et al., CogSci 2018) | 14 |
-| [`zinc250k`](zinc250k/README.md) | Molecular / Chemical | ZINC250k drug-likeness properties (Gómez-Bombarelli et al., ACS Cent. Sci. 2018) | 3 |
+| [`zinc250k`](zinc250k/README.md) | Molecular | ZINC250k drug-likeness properties (Gómez-Bombarelli et al., ACS Cent. Sci. 2018) | 3 |
 
 **Total: 55 datasets, 5011+ tasks**
 

jr/README.md

@@ -1,6 +1,6 @@
-# Joining Rows (JR)
+# JR
 
-Grid transformation tasks inspired by the Abstraction and Reasoning Corpus (ARC), encoded as ILP problems. Each task requires learning a program that computes integer output values by combining values from rows of the input grid using arithmetic operations. 250 tasks.
+List function tasks encoded as ILP problems. Each task requires learning a program that computes integer output values from a list of integer inputs using arithmetic operations. 250 tasks.
 
 **Tasks:** 250 task directories (`c001_1`, `c002_1`, …, `c250_1`), each with a `train/` split.