Explore my papers in Google Scholar - Ralf Brown.
Ralf D. Brown, "Augmentation" in K. Goodman, ed. KBMT-89 Project Report. Center for Machine Translation, Carnegie Mellon University. 1989.
Ralf D. Brown and Sergei Nirenburg, "Human-Computer Interaction for
Semantic Disambiguation". In Proceedings of the Thirteenth
International Conference on Computational Linguistics (COLING'90),
vol 3, pp. 42-47. Helsinki, Finland
[photos].
Available in Scribe and
PostScript format.
Abstract:
We describe a semi-automatic semantic disambiguator integrated in a
knowledge-based machine translation system. It is used to bridge the
analysis and generation stages in machine translation. The user
interface of the disambiguator is built on mouse-based
multiple-selection menus.
Ralf D. Brown. "Automatic and Interactive Augmentation". In K. Goodman and S. Nirenburg (ed), The KBMT Project: A Case Study in Knowledge-Based Machine Translation. Morgan Kaufmann Publishers, 1991. ISBN 1-55860-129-5.
Ralf D. Brown, "Automated Dictionary Extraction for ``Knowledge-Free''
Example-Based Translation". In Proceedings of the Seventh
International Conference on Theoretical and Methodological
Issues in Machine Translation, p. 111-118. Santa Fe, July 23-25, 1997.
(CiteSeer doi:10.1.1.48.1774)
Available in LaTeX and
PostScript format.
Abstract:
An Example-Based Machine Translation system is supplied with a
sentence-aligned bilingual corpus, but no other knowledge sources.
Using the knowledge implicit in the corpus, it generates a bilingual
word-for-word dictionary for alignment during translation. With such an
automatically-generated dictionary, the system covers (with equivalent
quality) more of its input on unseen texts than the same system
does when provided with a manually-created general-purpose dictionary
and other knowledge sources.
My COLING-ACL'98 paper is also relevant to EBMT.
Ralf D. Brown. "Adding Linguistic Knowledge to a Lexical Example-Based
Translation System". In Proceedings of the Eighth
International Conference on Theoretical and Methodological Issues in Machine
Translation
(TMI-99), p. 22-32.
Chester, UK
[photos],
August 1999. (CiteSeer doi:10.1.1.44.1381)
Available in
LaTeX and
PostScript format.
Abstract:
Example-Based Machine Translation (EBMT) using partial exact matching
against a database of translation examples has proven quite
successful, but requires a large amount of pre-translated text in
order to achieve broad coverage of unrestricted text. By adding
linguistically tagged entries to the example base and permitting
recursive matches that replace the matched text with the associated
tag, substantial reductions in the required amount of pre-translated
text can be achieved. A modest investment of time -- on the order of
two person-weeks -- adding linguistic knowledge reduces the required
example text by a factor of six or more, while retaining comparable
translation quality. This reduction makes EBMT more attractive for
so-called ``low-density'' languages for which little data is available.
Ralf Brown. "Example-Based Machine Translation at Carnegie Mellon
University". In The ELRA Newsletter, European Language Resources
Association, vol 5:1, January-March 2000.
Available in PDF format.
Ralf D. Brown. "Automated Generalization of Translation Examples".
In Proceedings of the Eighteenth International Conference on
Computational Linguistics (COLING-2000),
p. 125-131.
Saarbrücken, Germany
[photos],
August 2000. (CiteSeer doi:10.1.1.14.3211)
Available in
PostScript and
LaTeX format.
Abstract:
Previous work has shown that adding generalization of the examples in
the corpus of an example-based machine translation (EBMT) system can
reduce the required amount of pretranslated example text by as much as
an order of magnitude for Spanish-English and French-English EBMT.
Using word clustering to automatically generalize the example corpus
can provide the majority of this improvement for French-English with
no manual intervention; the prior work required a large tagged
bilingual dictionary and the manual creation of grammar rules. By
seeding the clustering with a small amount of manually-created
information, even better performance can be achieved. This paper
describes a method whereby bilingual word clustering can be performed
using standard monolingual document clustering techniques, and
its effectiveness at reducing the size of the example corpus required.
Ying Zhang,
Ralf D. Brown, and
Robert E. Frederking.
"Adapting an Example-Based Translation System to Chinese".
In Proceedings of
HLT 2001: First International
Conference on Human Language Technology Research, p. 7-10.
San Diego, California,
March 18-21, 2001.
Available in PostScript.
Abstract:
We describe an Example-Based Machine Translation (EBMT) system and the
adaptations and enhancements made to create a Chinese-English
translation system from the Hong Kong legal code and various other
bilingual resources available from the Linguistic Data Consortium (LDC).
Ralf D. Brown.
"Transfer-Rule Induction for Example-Based Translation".
In Proceedings of the
MT Summit VIII Workshop on Example-Based Machine Translation,
p. 1-11.
Santiago de Compostela, Spain, 18 September 2001. (CiteSeer doi:10.1.1.21.6724)
Available in PostScript.
Abstract:
Previous work has shown that grammars and similar structure can be
induced from unlabeled text (both monolingually and bilingually), and
that the performance of an example-based machine translation (EBMT)
system can be substantially enhanced by using clustering techniques to
determine equivalence classes of individual words which can be used
interchangeably, thus converting translation examples into
templates. This paper describes the combination of these two
approaches to further increase the coverage (or conversely, decrease
the required training text) of an EBMT system. Preliminary results
show that a reduction in required training text by a factor
of twelve is possible for translation from French into English.
Ying Zhang,
Ralf D. Brown,
Robert E. Frederking, and
Alon Lavie.
"Pre-processing of Bilingual Corpora for Mandarin-English EBMT".
In Proceedings of the
MT Summit VIII.
Santiago de Compostela, Spain, September 2001. (CiteSeer doi:10.1.1.67.4098)
Available in PostScript and
PDF.
Abstract:
Pre-processing of bilingual corpora plays an important role in
Example-Based Machine Translation (EBMT) and Statistical-Based Machine
Translation (SBMT). For our Mandarin-English EBMT system,
pre-processing includes segmentation for Mandarin, bracketing for
English and building a statistical dictionary from the corpus. In
this paper, we describe the work we have done to improve the
segmentation for Mandarin and the bracketing process for English to
increase the length of English phrases. The final results of the
corpus pre-processing are a segmented/bracketed aligned bilingual
corpus and a statistical dictionary. We achieved positive results by
increasing the average length of Chinese terms about 60% and 10% for
English. The statistical dictionary gained about a 30% increase in
coverage.
Rebecca Hutchinson,
Paul N. Bennett,
Jaime G. Carbonell,
Peter Jansen, Ralf Brown.
"Maximal Lattice Overlap in Example-Based Machine Translation",
Technical Report
CMU-CS-03-138/CMU-LTI-03-174, June 2003. (10.1.1.73.2384)
Abstract:
Example-Based Machine Translation (EBMT) retrieves pre-translated
phrases from a sentence-aligned bilingual training corpus to translate
new input sentences. EBMT uses long pre-translated phrases effectively
but is subject to disfluencies at phrasal translation boundaries. We
address this problem by introducing a novel method that exploits
overlapping phrasal translations and the increased confidence in
translation accuracy they imply. We specify an efficient algorithm for
producing translations using overlap. Finally, our empirical analysis
indicates that this approach produces higher quality translations than
the standard method of EBMT in a peak-to-peak comparison.
Ralf D. Brown,
Rebecca Hutchinson,
Paul N. Bennett,
Jaime G. Carbonell,
Peter Jansen.
"Reducing Boundary Friction Using Translation-Fragment Overlap",
in Proceedings of the Ninth Machine Translation Summit,
New Orleans,
USA, September 2003, pp. 24-31. (CiteSeer doi:10.1.1.68.7166)
Available in Postscript.
Abstract:
Many corpus-based Machine Translation (MT) systems generate a number
of partial translations which are then pieced together rather than
immediately producing one overall translation. While this makes them
more robust to ill-formed input, they are subject to disfluencies at
phrasal translation boundaries even for well-formed input. We address
this "boundary friction" problem by introducing a method that exploits
overlapping phrasal translations and the increased confidence in
translation accuracy they imply. We specify an efficient algorithm
for producing translations using overlap. Finally, our empirical
analysis indicates that this approach produces higher quality
translations than the standard method of combining non-overlapping
fragments generated by our Example-Based MT system in a peak-to-peak
comparison.
Ralf D. Brown. ``Clustered Transfer Rule Induction for Example-Based Translation''. In Michael Carl & Andy Way (eds.) Recent Advances in Example-Based Machine Translation (Dordrecht: Kluwer Academic Publishers, 2003), pp. 287-305.
Ralf D. Brown,
"A Modified Burrows-Wheeler Transform for Highly-Scalable Example-Based
Translation",
in Machine Translation: From Real Users to Research, Proceedings of
the 6th Conference of the Association for Machine Translation (AMTA-2004),
Washington, D.C.,
USA, September/October 2004, pp. 27-36. Springer, Lecture Notes in Artificial
Intelligence, Volume 3265, ISSN 0302-9743.
Available in Postscript and
PDF.
Abstract:
The Burrows-Wheeler Transform (BWT) was originally developed for data
compression, but can also be applied to indexing text. In this paper,
an adaptation of the BWT to word-based indexing of the training corpus
for an example-based machine translation (EBMT) system is presented.
The adapted BWT embeds the necessary information to retrieve matched
training instances without requiring any additional space and can be
instantiated in a compressed form which reduces disk space and memory
requirements by about 40% while still remaining searchable without
decompression.
Both the speed advantage from O(log N) lookups compared to the
O(N) lookups in the inverted-file index which had previously been
used and the structure of the index itself act as enablers for
additional capabilities and run-time speed. Because the BWT groups
all instances of any n-gram together, it can be used to quickly
enumerate the most-frequent n-grams, for which translations can be
precomputed and stored, resulting in an order-of-magnitude speedup at
run time.
Jae Dong Kim, Ralf D. Brown, Peter J. Jansen, and Jaime G. Carbonell. "Symmetric Probabilistic Alignment for Example-Based Translation". In Proceedings of the Tenth Workshop of the European Association for Machine Translation (EAMT-05), Budapest, Hungary, May 2005.
Ralf D. Brown.
"Context-Sensitive Retrieval for Example-Based Translation".
In Proceedings of the Tenth Machine Translation Summit
(MT Summit X), pp. 9-15. Phuket, September 2005.
Available in Postscript and PDF.
Abstract:
Example-Based Machine Translation (EBMT) systems have typically
operated on individual sentences without taking into account prior
context. By adding a simple reweighting of retrieved fragments of
training examples on the basis of whether the previous translation
retrieved any fragments from examples within a small window of the
current instance, translation performance is improved. A further
improvement is seen by performing a similar reweighting when another
fragment of the current input sentence was retrieved from the same
training example. Together, a simple, straightforward implementation
of these two factors results in an improvement on the order of
1.0-1.6% in the BLEU metric across multiple data sets in multiple
languages.
Ralf Brown and
Robert Frederking,
"Applying Statistical English Language Modelling to Symbolic Machine
Translation".
In Proceedings of the Sixth International Conference on Theoretical and
Methodological Issues in Machine Translation
(TMI'95), p. 221-239.
Leuven, Belgium, July 5-7, 1995. (CiteSeer doi:10.1.1.124.7392)
Available in LaTeX and
PostScript format.
Abstract:
The PANGLOSS Mark III system was from the outset designed
to be a symbolic, human-aided machine translation (MT) system. The
need arose to rapidly adapt it for use as a fully-automated MT system.
Our solution to this problem was to add a statistical English language
model (ELM) to replace the most significant user activity, selecting
between alternate translations produced by the system. The language
model used is a trigram model with backoff to bigram and unigram
probabilities. The language modeling and search procedure are
described in detail, and comparison is made to other trigram-based
statistical MT work.
Ralf D. Brown, "Automated Dictionary Extraction for ``Knowledge-Free''
Example-Based Translation".
In Proceedings of the Seventh International Conference on Theoretical and
Methodological Issues in Machine Translation, p. 111-118.
Santa Fe, July 23-25, 1997.
Available in LaTeX and
PostScript format.
Abstract:
An Example-Based Machine Translation system is supplied with a
sentence-aligned bilingual corpus, but no other knowledge sources.
Using the knowledge implicit in the corpus, it generates a bilingual
word-for-word dictionary for alignment during translation. With such an
automatically-generated dictionary, the system covers (with equivalent
quality) more of its input on unseen texts than the same system
does when provided with a manually-created general-purpose dictionary
and other knowledge sources.
Ralf D. Brown. "Automatically-Extracted Thesauri for Cross-Language IR:
When Better is Worse", In Proceedings of the First Workshop on Computational
Terminology (COMPUTERM'98),
Montreal, Canada
[photos],
15 August 1998, pp. 15-21. (CiteSeer doi:10.1.1.46.7633)
(Held in conjunction with
COLING-ACL'98).
Available in PostScript format (7 pages).
Rashmi Gangadharaiah, Ralf Brown and Jaime Carbonell.
"Monolingual Distributional Profiles for Word Substitution in Machine
Translation", in Proceedings of COLING-2010, August
23-27, 2010, Beijing, China.
Abstract:
Out-of-vocabulary (OOV) words present a significant challenge for
Machine Translation. For low-resource languages, limited training data
further increases the frequency of OOV words and degrades the quality
of the translations. Past approaches have suggested using stems or
synonyms for OOV words. Unlike the previous methods, we propose
handling not just the OOV words but rare words as well in an
Example-based Machine Translation (EBMT) paradigm. Presence of OOV
words and rare words in the input sentence prevents the system from
finding longer phrasal matches and produces low quality translations
due to less reliable language model estimates. The proposed method
requires only a monolingual corpus of the source language to find can-
didate replacements. A new framework is introduced to score and rank
the replacements by efficiently combining features extracted for the
candidate replacements. The lattice representation scheme allows the
decoder to select from a beam of possible replacement candidates. The
new framework gives statistically significant improvements in
English-Chinese and English-Haitian translation systems.
Kathy Baker, Steven Bethard, Michael Bloodgood, Ralf Brown,
Chris Callison-Burch, Glen Coppersmith, Bonnie Dorr, Wes Filardo,
Kendall Giles, Ann Irvine, Mike Kayser, Lori Levin, Justin Martineau,
Jim Mayfield, Scott Miller, Aaron Phillips, Andrew Philpot, Christine
Piatko, Lane Schwartz and David Zajic. Semantically Informed
Machine Translation (SIMT), Summer Camp for Applied Language
Exploration (SCALE) 2009 Summer Workshop Final Report. Tech report
number 002 for the Human Language Technology Center Of Excellence
(HLTCOE). PDF.
Katharina Probst,
Ralf Brown, Jaime Carbonell,
Alon Lavie,
Lori Levin,
and Erik Peterson.
"Design and Implementation of Controlled Elicitation for Machine Translation
of Low-density Languages", in Proceedings of the MT2010 workshop at
MT Summit 2001.
Santiago de Compostela, Spain, September 2001.
Available as PostScript
and PDF.
Lori Levin, Rodolfo Vega, Jaime Carbonell, Ralf Brown, Alon Lavie, Eliseo Cañulef, and Carolina Huenchullan. "Data Collection and Language Technologies for Mapudungun". In Proceedings of the Third International Conference on Language Resources and Evaluation (LREC-2002). Las Palmas, Gran Canaria, Spain, May 2002.
Jaime Carbonell,
Katharina Probst,
Erik Peterson,
Christian Monson,
Alon Lavie,
Ralf Brown, and Lori Levin.
"Automatic Rule Learning for Resource-Limited MT".
In Proceedings of the Fifth Conference of the Association for
Machine Translation in the Americas (AMTA 2002), pp. 1-10.
Tiburon, California,
October 8-12, 2002.
Available in
PostScript
and
PDF.
Abstract:
Machine translation of minority languages presents unique challenges,
including the paucity of bilingual training data and the unavailability
of linguistically-trained speakers. This paper focuses on a machine
learning approach to transfer-based MT, where data in the form of translations
and lexical assignments are elicited from bilingual speakers, and a
seeded version-space learning algorithm formulates and refines transfer
rules.
Christian Monson, Lori Levin, Rodolfo Vega, Ralf Brown, Ariadna Font Llitjós, Alon Lavie, Jaime Carbonell, Eliseo Cañulef, and Rosendo Huisca. "Data Collection and Analysis of Mapudungun Morphology for Spelling Correction". In Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC-2004).
Robert E. Frederking, Alan W Black, Ralf D. Brown, John Moody, and Eric Steinbrecher. "Field Testing the Tongues Speech-to-Speech Machine Translation System". In Proceedings of the Third International Conference on Language Resources and Evaluation (LREC-2002), pp. 160-164. Las Palmas, Gran Canaria, Spain, May 2002.
Robert Frederking, Alan W Black, Ralf Brown, Alexander Rudnicky, John Moody, and Eric Steinbrecher. "Speech Translation on a Tight Budget Without Enough Data". In ACL-02 Workshop on Speech-to-Speech Translation: Algorithms and Systems. Philadelphia, Pennsylvania, July 2002.
Alan W Black, Ralf Brown, Robert Frederking, Kevin Lenzo,
John Moody, Alexander Rudnicky, and Rita Singh, and Eric Steinbrecher.
"Rapid Development of Speech-to-Speech Translation Systems."
In Proceedings of ICSLP-2002. Denver, 2002.
Available in PDF.
Katharina Probst and Ralf D. Brown,
"Using Similarity Scoring to Improve the Bilingual Dictionary for
Word Alignment". In Proceedings of the 40th Annual Meeting of
the Association for Computational Linguistics (ACL-02), pp. 409-416.
Philadelphia,
Pennsylvania, July 7-10, 2002.
Available in PostScript and
PDF.
Abstract:
We describe an approach to improve the bilingual cooccurrence dictionary
that is used for word alignment, and evaluate the improved dictionary
using a version of the Competitive Linking algorithm. We demonstrate a
problem faced by the Competitive Linking algorithm and present an approach
to ameliorate it. In particular, we rebuild the bilingual dictionary
by clustering similar words in a language an assigning them a higher
cooccurrence score with a given word in the other language than each single
word would have otherwise. Experimental results show a significant improvement
in precision and recall for word alignment when the improved dictionary is
used.
Violetta Cavalli-Sforza, Ralf D. Brown, Jaime G. Carbonell, Peter J. Jansen, and Jae Dong Kim. "Challenges in Using an Example-Based MT System for a Transnational Digital Government Project". In Proceedings of the Ninth Workshop of the European Association for Machine Translation (EAMT-04), pp. 33-42. University of Malta, April 26-27, 2004.
Yiming Yang, Ralf D. Brown, Robert Frederking, Jaime Carbonell, Yibing Geng and Daniel Lee. "Bilingual-corpus Based Approaches to Translingual Information Retrieval". 2nd Workshop on Multilinguality in Software Industry: The AI Contribution (MULSAIC'97). Nagoya, Japan, August 25, 1997.
R.D. Brown, "Corpus-Based Query Translation for Translingual Information
Retrieval".
Position paper for SIGIR-97 workshop on Cross-Lingual
Information Retrieval (Philadelphia, 31 July 1997).
Available in LaTeX and
PostScript format. Overhead
transparencies from the workshop are also available in
Scribe and
PostScript format.
Ralf D. Brown. "Automatically-Extracted Thesauri for Cross-Language IR:
When Better is Worse", In Proceedings of the First Workshop on Computational
Terminology (COMPUTERM'98),
Montreal, Canada
[photos],
15 August 1998, pp. 15-21.
Available in PostScript format (7 pages).
Yiming Yang, Jaime G. Carbonell,
Ralf D. Brown, and
Robert E. Frederking.
"Translingual Information Retrieval: Learning from Bilingual Corpora",
In Artificial Intelligence, Special issue: Best of
IJCAI-97). Vol. 103 (1998), pp. 323-345.
(CiteSeer doi:10.1.1.42.8746)
Available in PostScript format (23 pages).
Ralf D. Brown, "Corpus-Driven Splitting of Compound Words",
In Proceedings of the Ninth International Conference on
Theoretical and Methodological Issues in Machine Translation (TMI-2002).
Keihanna, Japan [photos],
March 2002. (CiteSeer doi:10.1.1.13.3087)
Available in PostScript, PDF, and LaTeX formats (10 pages).
Abstract:
This paper presents a method for splitting compound words into their
constituents based on cognate words in the other language of a
parallel corpus. A minor extension to the method allows the
decompounding of words which do not have cognates in the other
language. By decompounding the training corpus for an Example-Based
MT system, the incidence of word alignment failure can be
substantially reduced, yielding a modest improvement in performance.
Ralf D. Brown, "Non-linear Mapping for Improved Identification of
1300+ Languages." In Proceedings of the Conference on Empirical
Methods in Natural Language Processing (EMNLP-2014).
(Preprint available on request)
Abstract:
Non-linear mappings of the form P(ngram)γ and
log(1+τ P(ngram))/log(1+τ) are applied to the n-gram
probabilities in five trainable open-source language identifiers. The
first mapping reduces classification errors by 4.0% to 83.9% over a
test set of more than one million 65-character strings in 1366
languages, and by 2.6% to 76.7% over a subset of 781 languages. The
second mapping improves four of the five identifiers by 10.6% to
83.8% on the larger corpus and 14.4% to 76.7% on the smaller
corpus. The subset corpus and the modified programs are made freely
available for download at http://www.cs.cmu.edu/~ralf/langid.html.
Jaime G. Carbonell,
Yiming Yang,
John Lafferty, Ralf Brown,
Tom Pierce, and
Xin Liu.
"CMU Report on
TDT-2:
Segmentation, Detection, and Tracking",
in
Proceedings of the 1999 DARPA Broadcast News Conference.
Available in HTML and
PostScript.
Yiming Yang, Jaime G. Carbonell, Ralf D. Brown, Thomas Pierce, Brian T. Archibald, and Xin Liu. "Learning Approaches for Detecting and Tracking News Events". In IEEE Intelligent Systems, Volume 14, Number 4, pp 32-43.
Ralf D. Brown, Thomas Pierce,
Yiming Yang, and
Jaime G. Carbonell.
"Link Detection - Results and Analysis", TDT-1999 workshop.
Available in HTML, Postcript, and LaTeX.
Ralf D. Brown,
"A Server for Real-Time Event Tracking in News".
In Proceedings of HLT 2001:
First International Conference on Human Language Technology Research,
p. 325-327.
San Diego, California,
March 18-21, 2001.
Available in PostScript.
Ralf D. Brown, "Dynamic Stopwording for Story Link Detection".
In Proceedings of HLT 2002:
Second International Conference on Human Language Technology Research, ed. Mitchell Marcus.
San Diego, California,
March 24-27, 2002, pp. 190-193. (CiteSeer doi:10.1.1.16.4523)
Draft version distributed to conference participants is available in
GZipped PostScript
(note -- 5.8 megs after decompressing, due to bitmapped graphs).
Abstract:
Carnegie Mellon University entered two systems in the Story Link
Detection track of the 2001 Topic Detection and Tracking (TDT)
evaluation. These systems were one of our systems from the 1999 TDT
evaluation, retuned for the new corpus, which had the
third-best cost measure; and a new system that adds clustering and
dynamically-generated stopwording, which had the best cost measure
among all submissions for the default evaluation condition. This
paper describes the enhancements which were made and some which
were attempted but not used in the evaluation.
Ralf Brown and Jim Kyle.
PC Interrupts: A Programmer's Reference to BIOS, DOS, and Third-Party
Calls.
Addison-Wesley, 1991, 1024 pp.
ISBN 0-201-57797-6.
(Chinese translation: ISBNs 957-652-272-2, 957-652-271-4, and 957-652-261-7;
Russian translation: ISBNs 5-03-002989-3 and 5-03-002990-7)
Errata are available.
A. Schulman, R. Brown,
D. Maxey, R.J. Michels, and
J. Kyle.
Undocumented DOS: A Programmer's Guide to Reserved MS-DOS Functions and
Data Structures, 2nd ed. Addison-Wesley,
1993. ISBN 0-201-63287-X.
Errata are available.
Ralf Brown and Jim Kyle.
PC Interrupts: A Programmer's Reference to BIOS, DOS, and Third-Party
Calls, 2nd ed. Addison-Wesley, 1994.
ISBN 0-201-62485-0.
Errata are available.
Ralf Brown and Jim Kyle.
Network Interrupts: A Programmer's Reference to Networking Calls.
Addison-Wesley, 1994.
ISBN 0-201-62644-6.
Errata are available.
Ralf Brown and Jim Kyle. Uninterrupted Interrupts: A Programmer's CD-ROM Reference to Network APIs and to BIOS, DOS, and Third-Party Calls. Addison-Wesley, 1994. ISBN 0-201-40966-6.
Ralf Brown, "QPI: The QEMM-386 Programming Interface". In Dr. Dobb's Journal, July 1994, pp. 123-131. Miller-Freeman, Inc., San Mateo, California. ISSN 0-38351-16562-8-07.
Ralf Brown. "A Swapping Replacement for the spawn() Family." In D. Burki and R. Ward, ed., MS-DOS System Programming, Third Edition. R&D Publications, 1994. ISBN 0-13-207382-X.
Ralf Brown, "Pentium Model-Specific Registers and What They Reveal". A binary of the High MSR display program (114 bytes) is also available.
A pair of Usenet articles posted on 29apr95: Generalized Feistel Networks and Sliding Feistel Networks.