Papers › Neural Variational Inference for Text Processing
Neural Variational Inference for Text Processing
Yishu Miao, Lei Yu, Phil Blunsom
Recent advances in neural variational inference have spawned a renaissance in deep latent variable models. In this paper we introduce a generic variational inference framework for generative and conditional models of text. While traditional variational methods derive an analytic approximation for the intractable distributions over latent variables, here we construct an inference network conditioned on the discrete text input to provide the variational distribution. We validate this framework on two very different text modelling applications, generative document modelling and supervised question answering. Our neural variational document model combines a continuous stochastic document representation with a bag-of-words generative model and achieves the lowest reported perplexities on two standard test corpora. The neural answer selection model employs a stochastic representation layer within an attention mechanism to extract the semantics between a question and answer pair. On two question answering benchmarks this model exceeds all previous published benchmarks.
In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.
For agents, Syntology's MCP tool lists every function and class Syntology harvested from this paper and whether it ran (how to connect): get_harvested_code_for_paper(arxiv_id="1511.06038")
Code
Syntology Ran 1 of 4 code samples harvested from 2 repositories linked to this paper; 3 have no recorded run. Of those that ran: 1 ran · our draft was wrong.
By repository: community (archive-listed): 4 samples from 2 repositories, 1 ran. The run record, sample by sample. “Ran” means executed on a synthesized input, not that the code is correct or reproduces the paper.
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
4 samples harvested; 1 ran; 0 honoured the contract we drafted; 3 have no recorded run. Read from Syntology's graph 2026-09-24; that is when this build read the record, not when the samples ran.
Licence: 1 of the 4 samples is pointer only, meaning Syntology does not serve that copy's text. This page shows no code text for any sample; each one links to its file in the repository.
Harvested from 2 repositories linked to this paper, official or community; each sample names its own and says which. “Ran” means the sample executed on a synthesized input. It does not mean the output is correct, and nothing here reproduces the paper's results. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code.
Each sample ends with its code_sha256, Syntology's identity for that exact code. An agent fetches the stored sample with Syntology's MCP tool get_code(code_sha256="…") (how to connect); click an identity to copy that call.
Repository labels, per sample. official repository: The archive marks this repository official for the paper. named in the paper: The archive records that the paper mentions this repository; it is not marked official. community (archive-listed): In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper. found in paper text by Syntology: Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted. community: Not in the archive's code links for this paper; a community repository Syntology harvested. Samples from a repository marked official are listed first. Licence labels name the repository's licence as recorded at harvest. “Pointer only” means Syntology does not serve that copy's text, for one of four reasons: no licence file was found; the licence was not identified; the licence is recorded as permissive but that copy's record is not marked cleared; or the licence is outside the permissive list Syntology serves text under (MIT, Apache-2.0, BSD and similar). Some licences outside that list permit redistribution, such as WTFPL, and GPL-3.0 under its conditions; they are simply not on the list. Hover a licence label for the reason. File links open the file on GitHub at the default branch, which may have changed since the harvest.
c7a758418e234da7 · report
1f8d62e9dcc2ed5b · report
96027a5753a7ea3c · report
ebd45c240000a52c · report
Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Question Answering | QASent | Attentive LSTM | MAP | 0.7339 | #1 of 7 | Archive leaderboard | report |
| Question Answering | QASent | Attentive LSTM | MRR | 0.8117 | #1 of 7 | Archive leaderboard | report |
| Question Answering | QASent | LSTM (lexical overlap + dist output) | MAP | 0.7228 | #2 of 7 | Archive leaderboard | report |
| Question Answering | QASent | LSTM (lexical overlap + dist output) | MRR | 0.7986 | #2 of 7 | Archive leaderboard | report |
| Question Answering | QASent | LSTM | MAP | 0.6436 | #5 of 7 | Archive leaderboard | report |
| Question Answering | QASent | LSTM | MRR | 0.7235 | #5 of 7 | Archive leaderboard | report |
| Question Answering | WikiQA | Attentive LSTM | MAP | 0.6886 | #15 of 25 | Archive leaderboard | report |
| Question Answering | WikiQA | Attentive LSTM | MRR | 0.7069 | #15 of 25 | Archive leaderboard | report |
| Question Answering | WikiQA | LSTM (lexical overlap + dist output) | MAP | 0.682 | #17 of 25 | Archive leaderboard | report |
| Question Answering | WikiQA | LSTM (lexical overlap + dist output) | MRR | 0.6988 | #17 of 25 | Archive leaderboard | report |
| Question Answering | WikiQA | LSTM | MAP | 0.6552 | #20 of 25 | Archive leaderboard | report |
| Question Answering | WikiQA | LSTM | MRR | 0.6747 | #20 of 25 | Archive leaderboard | report |
| Topic Models | 20 Newsgroups | NVDM | Test perplexity | 836 | #2 of 2 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections