Difference between revisions of "2012Q3 Reports: Program Chairs"
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The following table shows the number of submissions in each area for long and short papers, as well as the number of papers accepted in each area. | The following table shows the number of submissions in each area for long and short papers, as well as the number of papers accepted in each area. | ||
| − | {| class="wikitable" cellpadding="2" | + | {| class="wikitable" cellpadding="2" border="1" |
|+ Long Paper Submission Statistics | |+ Long Paper Submission Statistics | ||
|- | |- | ||
| Line 34: | Line 34: | ||
| QA ||2 ||10 ||11 ||1 ||0 ||1 ||0 ||10 ||9.09% ||0.00% ||9.09% | | QA ||2 ||10 ||11 ||1 ||0 ||1 ||0 ||10 ||9.09% ||0.00% ||9.09% | ||
|- | |- | ||
| − | | Social Media ||2 ||46 ||51 ||5 ||1 ||6 ||3 ||42 ||9.80% ||1.96% ||11.76% | + | | Social Media and Sentiment||2 ||46 ||51 ||5 ||1 ||6 ||3 ||42 ||9.80% ||1.96% ||11.76% |
|- | |- | ||
| Speech ||1 ||19 ||16 ||6 ||0 ||6 ||0 ||10 ||37.50% ||0.00% ||37.50% | | Speech ||1 ||19 ||16 ||6 ||0 ||6 ||0 ||10 ||37.50% ||0.00% ||37.50% | ||
| Line 44: | Line 44: | ||
| TOTAL ||30 ||690 ||571 ||82 ||29 ||111 ||5 ||455 ||14.36% ||5.08% ||19.61% | | TOTAL ||30 ||690 ||571 ||82 ||29 ||111 ||5 ||455 ||14.36% ||5.08% ||19.61% | ||
|} | |} | ||
| + | |||
| + | {| class="wikitable" cellpadding="2" border="1" | ||
| + | |+ Short Paper Submission Statistics | ||
| + | |- | ||
| + | !Track !!#ACs !!#Reviewers !!#Submissions !!#Oral !!#Poster !!#Oral+Poster !!#Withdrawn !!#Reject !!%Oral !!%Poster !!%Accept | ||
| + | |- | ||
| + | | Dialogue & Discourse ||2 ||39 ||23 ||1 ||3 ||4 ||1 ||18 ||4.35% ||13.04% ||17.39% | ||
| + | |- | ||
| + | | IE & IR ||3 ||85 ||37 ||3 ||5 ||8 ||0 ||29 ||8.11% ||13.51% ||21.62% | ||
| + | |- | ||
| + | | Language Resources ||1 ||17 ||13 ||1 ||2 ||3 ||0 ||10 ||7.69% ||15.38% ||23.08% | ||
| + | |- | ||
| + | | Lexical Semantics ||2 ||77 ||31 ||4 ||2 ||6 ||0 ||25 ||12.90% ||6.45% ||19.35% | ||
| + | |- | ||
| + | | Lexicon and Ontology ||2 ||21 ||12 ||1 ||0 ||1 ||1 ||10 ||8.33% ||0.00% ||8.33% | ||
| + | |- | ||
| + | | Machine Learning ||2 ||54 ||28 ||2 ||3 ||5 ||0 ||23 ||7.14% ||10.71% ||17.86% | ||
| + | |- | ||
| + | | MT ||4 ||86 ||56 ||4 ||9 ||13 ||1 ||42 ||7.14% ||16.07% ||23.21% | ||
| + | |- | ||
| + | | Multilingual ||2 ||42 ||15 ||4 ||0 ||4 ||0 ||11 ||26.67% ||0.00% ||26.67% | ||
| + | |- | ||
| + | | NLP Apps ||2 ||49 ||18 ||4 ||1 ||5 ||0 ||13 ||22.22% ||5.56% ||27.78% | ||
| + | |- | ||
| + | | Parsing ||2 ||66 ||36 ||9 ||0 ||9 ||0 ||27 ||25.00% ||0.00% ||25.00% | ||
| + | |- | ||
| + | | QA ||2 ||10 ||10 ||0 ||0 ||0 ||0 ||10 ||0.00% ||0.00% ||0.00% | ||
| + | |- | ||
| + | | Social Media and Sentiment ||2 ||46 ||32 ||3 ||3 ||6 ||1 ||25 ||9.38% ||9.38% ||18.75% | ||
| + | |- | ||
| + | | Speech ||1 ||19 ||12 ||1 ||0 ||1 ||0 ||11 ||8.33% ||0.00% ||8.33% | ||
| + | |- | ||
| + | | Summarization & Generation ||2 ||48 ||23 ||1 ||3 ||4 ||2 ||17 ||4.35% ||13.04% ||17.39% | ||
| + | |- | ||
| + | | Phonology/Morphology, Tagging and Chunking, Word Segmentation ||1 ||31 ||23 ||2 ||5 ||7 ||0 ||16 ||8.70% ||21.74% ||30.43% | ||
| + | |- | ||
| + | | TOTAL ||30 ||690 ||369 ||40 ||36 ||76 ||6 ||287 ||10.84% ||9.76% ||20.94% | ||
| + | |} | ||
| + | |||
| + | There will be two awards, one for the best long paper and one for the best long paper by a student. There were no obvious short papers qualifying as the best paper. The candidates for the best paper awards were nominated by the area chairs, who took into consideration the feedback they received from the reviewers on whether a paper might merit a best paper prize. The final awards were then selected by the program chairs, with help from a few extra reviewer. The recipients of the best paper awards will present their papers in a plenary session during the second day of the conference. | ||
| + | |||
| + | We are delighted to have two distinguished invited speakers: Dr. Aravind K. Joshi (Henry Salvatori Professor, Computer and Cognitive Science University of Pennsylvania), who will give a reflection talk about the past of ACLs: "Remembrance of ACLs Past", and Dr. Mark Johnson (Professor, Language Sciences (CORE) in the Department of Computing at Macquarie University), who will give a presentation on his view of where we are heading to the future: "Computational Linguistics: Where do We Go from Here?" In addition, the recipient of the ACL Lifetime Achievement Award will present a plenary lecture during the final day of the conference. | ||
| + | |||
| + | Finally, we note that especially for the short paper track many authors attempted to exploit length restrictions. For example, the space for author details was often omitted from the submitted version. ACL 13 needs to be more explicit about such exploits. | ||
Latest revision as of 07:35, 24 June 2012
Program Chairs (Chin-Yew Lin and Miles Osborne)
ACL 2012 received a total of 940 papers. Excluding non-qualifying submissions, 571 were submitted as long papers and 369 were submitted as short papers. A program committee of 30 area chairs assisted by 690 reviewers selected 111 (19.6%) long papers and 76 (20.9%) short papers for presentation in the conference. Among the accepted papers, 82 of the long papers and 40 of the short papers will have an oral presentation, and 29 of the long papers and 36 of the short papers will be presented as posters.
The long paper submission deadlines of ACL 2012 and NAACL-HLT 2012 was just one week apart. To reduce duplicated review efforts, we decided (with NAACL-HLT 2012 program chairs) that double submission was not allowed between ACL 2012 and NAACL-HLT 2012. However, we had almost the same number of long paper and short paper submissions as ACL-IJCNLP 2009 which was held in Singapore.
The following table shows the number of submissions in each area for long and short papers, as well as the number of papers accepted in each area.
| Track (Long Paper) | #ACs | #Reviewers | #Submissions | #Oral | #Poster | #Oral+Poster | #Withdrawn | #Reject | %Oral | %Poster | %Accept |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Dialogue & Discourse | 2 | 39 | 39 | 5 | 2 | 7 | 0 | 32 | 12.82% | 5.13% | 17.95% |
| IE & IR | 3 | 85 | 64 | 7 | 5 | 12 | 0 | 52 | 10.94% | 7.81% | 18.75% |
| Language Resources | 1 | 17 | 15 | 1 | 1 | 2 | 0 | 13 | 6.67% | 6.67% | 13.33% |
| Lexical Semantics | 2 | 77 | 38 | 7 | 2 | 9 | 0 | 29 | 18.42% | 5.26% | 23.68% |
| Lexicon and Ontology | 2 | 21 | 14 | 3 | 0 | 3 | 0 | 11 | 21.43% | 0.00% | 21.43% |
| Machine Learning | 2 | 54 | 56 | 9 | 2 | 11 | 1 | 44 | 16.07% | 3.57% | 19.64% |
| MT | 4 | 86 | 75 | 9 | 7 | 16 | 0 | 59 | 12.00% | 9.33% | 21.33% |
| Multilingual | 2 | 42 | 31 | 5 | 2 | 7 | 1 | 23 | 16.13% | 6.45% | 22.58% |
| NLP Apps | 2 | 49 | 41 | 5 | 1 | 6 | 0 | 35 | 12.20% | 2.44% | 14.63% |
| Parsing | 2 | 66 | 64 | 13 | 0 | 13 | 0 | 51 | 20.31% | 0.00% | 20.31% |
| QA | 2 | 10 | 11 | 1 | 0 | 1 | 0 | 10 | 9.09% | 0.00% | 9.09% |
| Social Media and Sentiment | 2 | 46 | 51 | 5 | 1 | 6 | 3 | 42 | 9.80% | 1.96% | 11.76% |
| Speech | 1 | 19 | 16 | 6 | 0 | 6 | 0 | 10 | 37.50% | 0.00% | 37.50% |
| Summarization & Generation | 2 | 48 | 20 | 2 | 2 | 4 | 0 | 16 | 10.00% | 10.00% | 20.00% |
| Phonology/Morphology, Tagging and Chunking, Word Segmentation | 1 | 31 | 36 | 4 | 4 | 8 | 0 | 28 | 11.11% | 11.11% | 22.22% |
| TOTAL | 30 | 690 | 571 | 82 | 29 | 111 | 5 | 455 | 14.36% | 5.08% | 19.61% |
| Track | #ACs | #Reviewers | #Submissions | #Oral | #Poster | #Oral+Poster | #Withdrawn | #Reject | %Oral | %Poster | %Accept |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Dialogue & Discourse | 2 | 39 | 23 | 1 | 3 | 4 | 1 | 18 | 4.35% | 13.04% | 17.39% |
| IE & IR | 3 | 85 | 37 | 3 | 5 | 8 | 0 | 29 | 8.11% | 13.51% | 21.62% |
| Language Resources | 1 | 17 | 13 | 1 | 2 | 3 | 0 | 10 | 7.69% | 15.38% | 23.08% |
| Lexical Semantics | 2 | 77 | 31 | 4 | 2 | 6 | 0 | 25 | 12.90% | 6.45% | 19.35% |
| Lexicon and Ontology | 2 | 21 | 12 | 1 | 0 | 1 | 1 | 10 | 8.33% | 0.00% | 8.33% |
| Machine Learning | 2 | 54 | 28 | 2 | 3 | 5 | 0 | 23 | 7.14% | 10.71% | 17.86% |
| MT | 4 | 86 | 56 | 4 | 9 | 13 | 1 | 42 | 7.14% | 16.07% | 23.21% |
| Multilingual | 2 | 42 | 15 | 4 | 0 | 4 | 0 | 11 | 26.67% | 0.00% | 26.67% |
| NLP Apps | 2 | 49 | 18 | 4 | 1 | 5 | 0 | 13 | 22.22% | 5.56% | 27.78% |
| Parsing | 2 | 66 | 36 | 9 | 0 | 9 | 0 | 27 | 25.00% | 0.00% | 25.00% |
| QA | 2 | 10 | 10 | 0 | 0 | 0 | 0 | 10 | 0.00% | 0.00% | 0.00% |
| Social Media and Sentiment | 2 | 46 | 32 | 3 | 3 | 6 | 1 | 25 | 9.38% | 9.38% | 18.75% |
| Speech | 1 | 19 | 12 | 1 | 0 | 1 | 0 | 11 | 8.33% | 0.00% | 8.33% |
| Summarization & Generation | 2 | 48 | 23 | 1 | 3 | 4 | 2 | 17 | 4.35% | 13.04% | 17.39% |
| Phonology/Morphology, Tagging and Chunking, Word Segmentation | 1 | 31 | 23 | 2 | 5 | 7 | 0 | 16 | 8.70% | 21.74% | 30.43% |
| TOTAL | 30 | 690 | 369 | 40 | 36 | 76 | 6 | 287 | 10.84% | 9.76% | 20.94% |
There will be two awards, one for the best long paper and one for the best long paper by a student. There were no obvious short papers qualifying as the best paper. The candidates for the best paper awards were nominated by the area chairs, who took into consideration the feedback they received from the reviewers on whether a paper might merit a best paper prize. The final awards were then selected by the program chairs, with help from a few extra reviewer. The recipients of the best paper awards will present their papers in a plenary session during the second day of the conference.
We are delighted to have two distinguished invited speakers: Dr. Aravind K. Joshi (Henry Salvatori Professor, Computer and Cognitive Science University of Pennsylvania), who will give a reflection talk about the past of ACLs: "Remembrance of ACLs Past", and Dr. Mark Johnson (Professor, Language Sciences (CORE) in the Department of Computing at Macquarie University), who will give a presentation on his view of where we are heading to the future: "Computational Linguistics: Where do We Go from Here?" In addition, the recipient of the ACL Lifetime Achievement Award will present a plenary lecture during the final day of the conference.
Finally, we note that especially for the short paper track many authors attempted to exploit length restrictions. For example, the space for author details was often omitted from the submitted version. ACL 13 needs to be more explicit about such exploits.