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sa.track('MediaPageVIew', {media_event_value: window.appletSa}) |
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}</script><script>var __assign = (this && this.__assign) || function () { |
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function setProperty(option) { |
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var _a = option.data, data = _a === void 0 ? {} : _a, key = option.key, value = option.value, control = option.control, elseValue = option.elseValue; |
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Platform["H5"] = "H5"; |
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Platform["WEB"] = "web"; |
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})(Platform || (Platform = {})); |
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; |
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function judgePlatform(userAgent) { |
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if (!userAgent && typeof window !== 'undefined') { |
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userAgent = navigator.userAgent; |
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} |
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if (!userAgent) |
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return Platform.WEB; |
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if (userAgent.match(/iPad|iPhone/i)) { |
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return Platform.H5; |
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} |
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else if (userAgent.match(/Android/i)) { |
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return Platform.H5; |
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} |
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return Platform.WEB; |
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} |
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function externalLink(hrefValue) { |
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var data = {}; |
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var externalLinkList = [ |
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{ pathKey: '/', mediaSourceValue: 'page_home' }, |
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{ pathKey: 'p', mediaSourceValue: 'article' }, |
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|
{ pathKey: 'newsflashes', mediaSourceValue: 'newsflash', subPathNotNumMediaSourceValue: 'page_newsflashes' }, |
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{ pathKey: 'topics', mediaSourceValue: 'topics' }, |
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]; |
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var pathInfo = new PathInfo(window.location.pathname); |
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data.media_content_id = hrefValue; |
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Object.assign(data, setProperty({ |
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control: isNumber(pathInfo.sub), |
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key: 'source_id', |
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value: pathInfo.sub, |
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|
})); |
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|
if (pathInfo.root === 'local') { |
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data.media_event_value = 'local_' + pathInfo.sub; |
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} |
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return Object.assign(data, genMediaSource(externalLinkList, isNumber(pathInfo.sub))); |
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} |
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function internalLink(hrefValue, className) { |
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var pageInfo = new PageInfo(hrefValue); |
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var data = {}; |
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|
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Object.assign(data, setProperty({ |
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|
control: pageInfo.currentPath.sub && isNumber(pageInfo.currentPath.sub) && pageInfo.destPath.sub && isNumber(pageInfo.destPath.sub), |
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|
key: 'source_id', |
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|
value: pageInfo.currentPath.sub, |
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|
})); |
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|
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Object.assign(data, genMediaEventValue(hrefValue)); |
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|
|
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|
Object.assign(data, setProperty({ |
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|
control: pageInfo.currentPath.root === 'p' && isNumber(pageInfo.currentPath.sub) && isNumber(pageInfo.destPath.sub), |
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|
key: 'media_source', |
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|
value: 'article', |
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|
})); |
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|
|
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|
Object.assign(data, intoDetailPage(pageInfo.destPath.sub)); |
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|
|
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|
Object.assign(data, genContentTypeAndId(hrefValue, className)); |
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|
return data; |
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|
} |
|
|
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|
|
|
|
|
|
function genMediaEventValue(hrefValue) { |
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|
var data = {}; |
|
|
var key = 'media_event_value'; |
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|
var pageInfo = new PageInfo(hrefValue); |
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|
var genMediaEventValueList = [ |
|
|
{ pathKey: 'search', subPathList: [ |
|
|
{ key: 'articles', value: 'search_articles' }, |
|
|
{ key: 'newsflashes', value: 'search_flashnews' }, |
|
|
{ key: 'video', value: 'search_videos' }, |
|
|
{ key: 'monographic', value: 'search_topics' }, |
|
|
{ key: 'user', value: 'search_writer' }, |
|
|
] }, |
|
|
{ pathKey: 'information', subPathList: [ |
|
|
'web_news', 'contact', 'enterpriseservice', 'happy_life', 'travel', |
|
|
'real_estate', 'web_recommend', 'technology', { key: 'zhichang', value: 'web_zhichang' }, 'innovate', |
|
|
] }, |
|
|
{ pathKey: 'local' } |
|
|
]; |
|
|
for (var _i = 0, genMediaEventValueList_1 = genMediaEventValueList; _i < genMediaEventValueList_1.length; _i++) { |
|
|
var pathItem = genMediaEventValueList_1[_i]; |
|
|
if (pageInfo.currentPath.root === pathItem.pathKey) { |
|
|
if (pageInfo.currentPath.root === 'local') { |
|
|
|
|
|
data.media_event_value = 'local_' + pageInfo.currentPath.sub; |
|
|
} |
|
|
else { |
|
|
for (var _a = 0, _b = pathItem.subPathList; _a < _b.length; _a++) { |
|
|
var subPathItem = _b[_a]; |
|
|
var value = isObj(subPathItem) ? subPathItem.value : subPathItem; |
|
|
var subPathKey = isObj(subPathItem) ? subPathItem.key : subPathItem; |
|
|
if (pageInfo.currentPath.sub === subPathKey) { |
|
|
Object.assign(data, setProperty({ |
|
|
control: isNumber(pageInfo.destPath.sub), |
|
|
key: key, |
|
|
value: value, |
|
|
})); |
|
|
} |
|
|
} |
|
|
} |
|
|
} |
|
|
} |
|
|
return data; |
|
|
} |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
function intoDetailPage(subHref) { |
|
|
var pathInfo = new PathInfo(window.location.pathname); |
|
|
var intoDetailPageList = [ |
|
|
{ pathKey: '/', mediaSourceValue: 'page_home' }, |
|
|
{ pathKey: '/video', mediaSourceValue: 'page_video' }, |
|
|
{ pathKey: '/topics', mediaSourceValue: 'page_topics' }, |
|
|
{ pathKey: 'newsflashes', control: isNumber(pathInfo.sub), mediaSourceValue: 'newsflash', subPathNotNumMediaSourceValue: 'page_newsflashes' }, |
|
|
{ pathKey: 'information', mediaSourceValue: 'page_information' }, |
|
|
{ pathKey: 'search', mediaSourceValue: 'page_search' }, |
|
|
{ pathKey: 'Calendar', mediaSourceValue: 'calendar' }, |
|
|
{ pathKey: 'user', mediaSourceValue: 'user' }, |
|
|
{ pathKey: 'motif', mediaSourceValue: 'motif' }, |
|
|
{ pathKey: 'topics', mediaSourceValue: 'topics' }, |
|
|
{ pathKey: 'video', mediaSourceValue: 'video' }, |
|
|
{ pathKey: 'audio', mediaSourceValue: 'audio' }, |
|
|
]; |
|
|
return genMediaSource(intoDetailPageList, isNumber(subHref)); |
|
|
} |
|
|
|
|
|
|
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|
|
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|
|
|
|
function genMediaSource(pathList, control) { |
|
|
var pathInfo = new PathInfo(window.location.pathname); |
|
|
var key = 'media_source'; |
|
|
var data = {}; |
|
|
for (var _i = 0, pathList_1 = pathList; _i < pathList_1.length; _i++) { |
|
|
var pathItem = pathList_1[_i]; |
|
|
if (pathInfo.path === pathItem.pathKey) { |
|
|
data.media_source = pathItem.mediaSourceValue; |
|
|
} |
|
|
else if (pathInfo.root === pathItem.pathKey && pathInfo.sub) { |
|
|
Object.assign(data, setProperty({ |
|
|
control: objHasKey(pathItem, 'control') ? pathItem.control : control, |
|
|
key: key, |
|
|
value: pathItem.mediaSourceValue, |
|
|
elseValue: pathItem.subPathNotNumMediaSourceValue || null, |
|
|
})); |
|
|
} |
|
|
} |
|
|
return data; |
|
|
} |
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
function genContentTypeAndId(hrefValue, className) { |
|
|
|
|
|
var pageInfo = new PageInfo(hrefValue); |
|
|
var genContentTypeAndIdList = [ |
|
|
{ |
|
|
key: 'p', |
|
|
setData: { |
|
|
media_content_type: 'article', |
|
|
media_content_id: pageInfo.destPath.sub, |
|
|
} |
|
|
}, |
|
|
{ |
|
|
key: 'newsflashes', |
|
|
setData: { |
|
|
media_content_type: 'flashnews', |
|
|
media_content_id: pageInfo.destPath.sub, |
|
|
} |
|
|
}, |
|
|
{ |
|
|
key: 'video', |
|
|
setData: { |
|
|
media_content_type: 'video', |
|
|
media_content_id: pageInfo.destPath.sub, |
|
|
} |
|
|
}, |
|
|
{ |
|
|
key: 'v-video', |
|
|
setData: { |
|
|
media_content_type: 'video_portrait', |
|
|
media_content_id: pageInfo.destPath.sub, |
|
|
} |
|
|
}, |
|
|
{ |
|
|
key: 'topics', |
|
|
setData: { |
|
|
media_content_type: 'topic', |
|
|
media_content_id: pageInfo.destPath.sub, |
|
|
} |
|
|
}, |
|
|
{ |
|
|
key: 'motif', |
|
|
setData: { |
|
|
media_content_type: (function () { |
|
|
|
|
|
var isMotifList = pageInfo.currentPath.root === 'motif-catalog' && pageInfo.currentPath.sub === 'recomend'; |
|
|
var isHomeEntry = className.includes('businessMotifHome-main-item-top-a'); |
|
|
var isBusinessMotif = isMotifList || isHomeEntry; |
|
|
return isBusinessMotif ? 'business_motif' : 'motif'; |
|
|
})(), |
|
|
media_content_id: pageInfo.destPath.sub, |
|
|
} |
|
|
}, |
|
|
{ |
|
|
key: 'user', |
|
|
setData: { |
|
|
media_content_type: 'user', |
|
|
media_content_id: pageInfo.destPath.sub, |
|
|
} |
|
|
}, |
|
|
{ |
|
|
key: 'column', |
|
|
setData: { |
|
|
media_content_type: 'audio', |
|
|
media_content_id: pageInfo.destPath.sub, |
|
|
} |
|
|
}, |
|
|
]; |
|
|
var data = {}; |
|
|
if (!isNumber(pageInfo.destPath.sub)) |
|
|
return data; |
|
|
for (var _i = 0, genContentTypeAndIdList_1 = genContentTypeAndIdList; _i < genContentTypeAndIdList_1.length; _i++) { |
|
|
var hrefItem = genContentTypeAndIdList_1[_i]; |
|
|
if (pageInfo.destPath.root === hrefItem.key) { |
|
|
data = hrefItem.setData; |
|
|
} |
|
|
} |
|
|
return data; |
|
|
} |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
function genPropertyAccordingToAttribute(elementTarget) { |
|
|
|
|
|
var operation_list = elementTarget.getAttribute('sensors_operation_list'); |
|
|
|
|
|
var index_num = elementTarget.getAttribute('sensors_index_num'); |
|
|
|
|
|
var operate_type = elementTarget.getAttribute('sensors_operate_type'); |
|
|
|
|
|
var position_id = elementTarget.getAttribute('sensors_position_id'); |
|
|
|
|
|
var plan_id = elementTarget.getAttribute('sensors_media_content_id'); |
|
|
var genPropertyAccordingToAttributeList = [ |
|
|
{ |
|
|
control: operation_list === 'page_flow' && window.location.pathname === '/', |
|
|
key: 'operation_list', |
|
|
value: 'latest_articles', |
|
|
elseValue: 'page_flow' |
|
|
}, |
|
|
{ |
|
|
control: operation_list === 'banner', |
|
|
key: 'operation_list', |
|
|
value: 'banner' |
|
|
}, |
|
|
{ |
|
|
control: operation_list === 'banner_right', |
|
|
key: 'operation_list', |
|
|
value: 'banner_right' |
|
|
}, |
|
|
{ |
|
|
control: operation_list === 'author_latest_article', |
|
|
key: 'operation_list', |
|
|
value: 'author_latest_article' |
|
|
}, |
|
|
{ |
|
|
control: operation_list === 'specialtopic_recommend', |
|
|
key: 'operation_list', |
|
|
value: 'specialtopic_recommend' |
|
|
}, |
|
|
{ |
|
|
control: operation_list === 'video_recommend', |
|
|
key: 'operation_list', |
|
|
value: 'video_recommend' |
|
|
}, |
|
|
{ |
|
|
control: operation_list === 'dailyword', |
|
|
key: 'operation_list', |
|
|
value: 'dailyword' |
|
|
}, |
|
|
{ |
|
|
control: operation_list === 'latest_newsflash', |
|
|
key: 'operation_list', |
|
|
value: 'latest_newsflash' |
|
|
}, |
|
|
{ |
|
|
control: operation_list === 'business_motif', |
|
|
key: 'operation_list', |
|
|
value: 'business_motif' |
|
|
}, |
|
|
{ |
|
|
control: operation_list === 'hotlist', |
|
|
key: 'operation_list', |
|
|
value: 'hotlist' |
|
|
}, |
|
|
{ |
|
|
control: operation_list === 'latest_videos', |
|
|
key: 'operation_list', |
|
|
value: 'latest_videos' |
|
|
}, |
|
|
{ |
|
|
control: operation_list === 'recommend_motif', |
|
|
key: 'operation_list', |
|
|
value: 'recommend_motif' |
|
|
}, |
|
|
{ |
|
|
control: operation_list === 'hot_author', |
|
|
key: 'operation_list', |
|
|
value: 'hot_author' |
|
|
}, |
|
|
{ |
|
|
control: operation_list === 'next_card', |
|
|
key: 'operation_list', |
|
|
value: 'next_card' |
|
|
}, |
|
|
{ |
|
|
control: index_num, |
|
|
key: 'media_index_number', |
|
|
value: index_num |
|
|
}, |
|
|
{ |
|
|
control: operate_type, |
|
|
key: 'operate_type', |
|
|
value: operate_type |
|
|
}, |
|
|
{ |
|
|
control: position_id, |
|
|
key: 'position_id', |
|
|
value: position_id |
|
|
}, |
|
|
{ |
|
|
control: plan_id, |
|
|
key: 'media_content_id', |
|
|
value: plan_id |
|
|
}, |
|
|
{ |
|
|
control: operate_type || position_id, |
|
|
key: 'media_content_type', |
|
|
value: 'ad' |
|
|
}, |
|
|
{ |
|
|
control: position_id === '827' || operation_list === 'home_top', |
|
|
key: 'operation_list', |
|
|
value: 'home_top' |
|
|
}, |
|
|
{ |
|
|
control: position_id === '817', |
|
|
key: 'operation_list', |
|
|
value: 'article_bottom' |
|
|
}, |
|
|
{ |
|
|
control: position_id === '835', |
|
|
key: 'operation_list', |
|
|
value: 'comment_bottom' |
|
|
}, |
|
|
]; |
|
|
var data = {}; |
|
|
for (var _i = 0, genPropertyAccordingToAttributeList_1 = genPropertyAccordingToAttributeList; _i < genPropertyAccordingToAttributeList_1.length; _i++) { |
|
|
var infoItem = genPropertyAccordingToAttributeList_1[_i]; |
|
|
Object.assign(data, setProperty(infoItem)); |
|
|
} |
|
|
return data; |
|
|
} |
|
|
|
|
|
function manualMain(elementTarget) { |
|
|
if (elementTarget.tagName.toLowerCase() !== 'a') |
|
|
throw Error('目前只收集点击a标签所跳转的信息'); |
|
|
|
|
|
var data = { |
|
|
platform: judgePlatform(window && |
|
|
window.initialState && |
|
|
window.initialState.navigator && |
|
|
window.initialState.navigator.userAgent) |
|
|
}; |
|
|
var attributes = elementTarget.attributes; |
|
|
var hrefObj = attributes.href || {}; |
|
|
var className = getClass(attributes); |
|
|
var hrefValue = hrefObj.value || ""; |
|
|
if ((/(http|ftp|https):\/\//.test(hrefValue) && !hrefValue.includes('36kr.com')) || |
|
|
(/(http|ftp|https):\/\//.test(hrefValue) && hrefValue.includes('36kr.com/api/ad/'))) { |
|
|
Object.assign(data, externalLink(hrefValue)); |
|
|
} |
|
|
else { |
|
|
var internalLinkHrefValue = hrefValue; |
|
|
if (hrefValue.includes('36kr.com')) |
|
|
internalLinkHrefValue = hrefValue.split('36kr.com')[1]; |
|
|
Object.assign(data, internalLink(internalLinkHrefValue, className)); |
|
|
} |
|
|
|
|
|
Object.assign(data, genPropertyAccordingToAttribute(elementTarget)); |
|
|
return data; |
|
|
} |
|
|
|
|
|
|
|
|
|
|
|
var PathInfo = (function () { |
|
|
function PathInfo(path) { |
|
|
this.path = path; |
|
|
var pathArr = path.split('/').filter(function (x) { return x !== ""; }); |
|
|
this.root = pathArr[0]; |
|
|
this.sub = pathArr[1]; |
|
|
} |
|
|
return PathInfo; |
|
|
}()); |
|
|
|
|
|
var PageInfo = (function () { |
|
|
function PageInfo(href) { |
|
|
this.destPath = __assign({}, new PathInfo(href), new SourcePath(href)); |
|
|
this.currentPath = __assign({}, new PathInfo(window.location.pathname), new SourcePath(window.location.pathname)); |
|
|
} |
|
|
return PageInfo; |
|
|
}()); |
|
|
var SourcePath = (function () { |
|
|
function SourcePath(href) { |
|
|
this.group = SourcePath.groupFn(href); |
|
|
} |
|
|
SourcePath.groupFn = function (href) { |
|
|
var pathInfo = new PathInfo(href); |
|
|
if (pathInfo.sub && isNumber(pathInfo.sub)) { |
|
|
return 'content'; |
|
|
} |
|
|
else { |
|
|
return 'default'; |
|
|
} |
|
|
}; |
|
|
return SourcePath; |
|
|
}()); |
|
|
|
|
|
function getCaseKey(data) { |
|
|
if (data.hasOwnProperty('operate_type') || |
|
|
data.hasOwnProperty('position_id')) { |
|
|
return 'MediaWebAD'; |
|
|
} |
|
|
else { |
|
|
return 'MediaWebRead'; |
|
|
} |
|
|
} |
|
|
function coverTagAClickEvent() { |
|
|
|
|
|
document.getElementById('app').addEventListener('click', function (e) { |
|
|
|
|
|
var event = e || window.event; |
|
|
var eventPath = event.path || []; |
|
|
var target = eventPath.filter(function (x) { |
|
|
return x && x.nodeName && x.nodeName.toLocaleLowerCase() === 'a'; |
|
|
}); |
|
|
|
|
|
if (target.length !== 0) { |
|
|
var elementTarget = target[target.length - 1]; |
|
|
if (elementTarget.getAttribute('sensors_do_not_send_data')) |
|
|
return; |
|
|
var targetValue_1 = elementTarget.getAttribute('target'); |
|
|
var targetHref = elementTarget.getAttribute('href'); |
|
|
var url_1 = elementTarget.href; |
|
|
var data = manualMain(elementTarget); |
|
|
if (!targetHref) |
|
|
return; |
|
|
if (!targetValue_1) |
|
|
e.preventDefault(); |
|
|
if (window.sa && window.sa.track) { |
|
|
window.sa.track(getCaseKey(data), data, function () { |
|
|
if (!targetValue_1) |
|
|
location.href = url_1; |
|
|
}); |
|
|
} |
|
|
else { |
|
|
if (!targetValue_1) |
|
|
location.href = url_1; |
|
|
} |
|
|
} |
|
|
}); |
|
|
|
|
|
} |
|
|
|
|
|
window.onload = function () { |
|
|
setTimeout(function () { |
|
|
coverTagAClickEvent(); |
|
|
}, 0); |
|
|
}; |
|
|
|
|
|
</script><script charset=utf-8 src=//static.36krcdn.com/36kr-web/static/0.1b18914b.js></script><script charset=utf-8 src=//static.36krcdn.com/36kr-web/static/1.912ad9fa.js></script><script charset=utf-8 src=//static.36krcdn.com/36kr-web/static/article.b89f7102.js></script><meta content=article data-react-helmet=true property=og:type><meta content=https://36kr.com/p/3213104463187073 data-react-helmet=true property=og:url><style>@keyframes circle_classic{0%{opacity: 0.1;transform: rotate(0deg) scale(0.5);}100%{opacity: 1;transform: rotate(360deg) scale(1.2);};}@keyframes typing{0%{background-color: rgba(158,158,158, 1);box-shadow: 12px 0px 0px 0px rgba(158,158,158,0.2),24px 0px 0px 0px rgba(158,158,158,0.2);}25%{background-color: rgba(158,158,158, 0.4);box-shadow: 12px 0px 0px 0px rgba(158,158,158,2),24px 0px 0px 0px rgba(158,158,158,0.2);}75%{background-color: rgba(158,158,158, 0.4);box-shadow: 12px 0px 0px 0px rgba(158,158,158,0.2),24px 0px 0px 0px 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class=i-want-contribution-icon></span><span class=i-want-contribution-text>我要入驻</span></div></div><a rel="noopener noreferrer nofollow"class=station-business href=/station-business target=_blank><span class=station-business-icon></span><span class=station-business-text>城市合作</span></a></div></div></div></div><div class=main-right><div class=kr-layout-content><div class=kr-article><div class=kr-article-inner><div class=article-detail-wrapper-box><div><div class=article-left-container><div class=article-content><div class=article-mian-content><div class="article-wrapper common-width"><div class=common-width><div><h1 class="article-title margin-bottom-20 common-width">AI一周写出ICLR研讨会论文，成果简洁有效获审稿人大赞</h1><div class="article-title-icon common-width margin-bottom-40"><a class="title-icon-item item-a"rel="nofollow noopener noreferrer"href=/user/1852809498 target=_blank>量子位</a><span class="title-icon-item item-time"><i>·</i>2025年03月19日 19:56</span></div><div class=summary>同行评审得分7/6/7</div></div></div><div class="common-width margin-bottom-20"><div class="common-width content articleDetailContent kr-rich-text-wrapper"><p>AI写的论文已经在ICLR的研讨会上通过了同行评审，还是一口气中就中了两篇。<p>其中一篇获得了<strong>7/6/7</strong>的同行评审分数，另一篇的审稿人也给出了<strong>7/7</strong>的成绩。<p>而且从假设生成到同行评审出版整个流程都是AI自主完成，<strong>一篇用时仅需不到一周</strong>。<p class=image-wrapper><img data-img-size-val=1080,744 src=https://img.36krcdn.com/hsossms/20250319/v2_d323924d9ec5492caa1715ef16a25c87@5888275_oswg359511oswg1080oswg744_img_000?x-oss-process=image/format,jpg/interlace,1><p>这个“AI科学家”名为<strong>Zochi</strong>，由名为的Intology初创企业打造，成立刚刚不到两个月。<p>两名联创分别是连续创业者<strong>Ron Arel</strong>和前Meta华人研究员<strong>Andy Zhou</strong>，两人均毕业于伊利诺伊大学厄巴纳-香槟分校。<p class=image-wrapper><img data-img-size-val=1080,756 src=https://img.36krcdn.com/hsossms/20250319/v2_3cf7eac7ed4647caba082bfbd56e907e@5888275_oswg367711oswg1080oswg756_img_000?x-oss-process=image/format,jpg/interlace,1><p>Zochi入选的两篇论文，是以Andy Zhou名义进行投稿的，内容分别是：<p><strong>子空间级别微调方法CS-ReFT</strong>，能够让7B的Llama-2在AlpacaEval中超过GPT-3.5，同行评审7/6/7；<p><strong>大模型安全漏洞检测框架Siege</strong>，针对GPT-3.5-Turbo的检测准确率为100%，审稿人打分7/7。<p>并且在基于NeurIPS规则的自动打分程序的评审中，Zochi<strong>两篇论文均获得了8分的成绩</strong>。<h2><strong>两篇论文入选ICLR</strong></h2><p>Zochi被ICLR研讨会相中的两篇论文具体内容，接下来就一起来了解~<h4><strong>让7B Llama-2超越GPT-3.5</strong></h4><p>第一篇论文，提出了一种名为CS-ReFT的子空间级别微调方法。<p class=image-wrapper><img data-img-size-val=1080,730 src=https://img.36krcdn.com/hsossms/20250319/v2_958c707844764694a685658ddada5466@5888275_oswg156049oswg1080oswg730_img_000?x-oss-process=image/format,jpg/interlace,1><p>Zochi发现了AI发展中的一个关键瓶颈——<strong>参数高效微调中的跨技能干扰</strong>。<p>也就是说，当同时将模型应用于多个任务时，一项技能的改进往往会降低其他技能的性能。<p>研究之后，Zochi提出了CS-ReFT方法，部分基于ReFT改造而来，但重点是表示编辑而不是权重修改。<p>具体来说，不同于LoRA等方法在权重级别实现正交性约束，CS-ReFT将这些约束直接应用于隐藏状态表示。<p>这种方法使得<strong>每个任务都有其专用的子空间变换</strong>，反之，每个变换都专注于一项独特的技能，从而消除了跨技能干扰。<p class=image-wrapper><img data-img-size-val=1080,601 src=https://img.36krcdn.com/hsossms/20250319/v2_4a3f229df64a47dcae4b13144dc7c42c@5888275_oswg107118oswg1080oswg601_img_000?x-oss-process=image/format,jpg/interlace,1><p>当应用于Llama-2-7B时，CS-ReFT在AlpacaEval上取得了93.94%的胜率，<strong>用不到万分之一的参数超过了GPT-3.5-Turbo</strong>（86.30%）。<p class=image-wrapper><img data-img-size-val=1034,944 src=https://img.36krcdn.com/hsossms/20250319/v2_4ef6f3d7ba0a4938ab1765194a6f7c77@5888275_oswg101859oswg1034oswg944_img_000?x-oss-process=image/format,jpg/interlace,1><p>评审人员称赞，这是一个“聪明的想法”，并且“有效解决了ReFT 的一个关键限制”。<h4><strong>发现大模型安全漏洞</strong></h4><p>第二篇论文，关于<strong>大模型安全</strong>。<p>从现有的安全文献出发，Zochi提出了Siege框架，它<strong>使用树搜索算法增强了多轮越狱策略</strong>。<p class=image-wrapper><img data-img-size-val=1080,745 src=https://img.36krcdn.com/hsossms/20250319/v2_92dda0dd376b4836add432f922b5785a@5888275_oswg150705oswg1080oswg745_img_000?x-oss-process=image/format,jpg/interlace,1><p>Zochi发现，模型在轻度违规在对话中累积的过程中会表现出“部分服从”行为，即在看似维护安全规则的同时附带产生一些违规的信息片段。<p>Siege就是利用这种现象，系统地识别和利用对话分支中的轻微违规，通过积累实现越狱攻击。<p>它将每个对话状态视为搜索树中的一个节点，采用定向搜索来并行探索多种攻击策略。<p>该框架其核心创新是一种复杂的部分合规性跟踪机制，可以识别和利用增量政策泄漏。<p class=image-wrapper><img data-img-size-val=1038,684 src=https://img.36krcdn.com/hsossms/20250319/v2_33240ab8635c4837b6550a44f469e388@5888275_oswg167583oswg1038oswg684_img_000?x-oss-process=image/format,jpg/interlace,1><p>与以前的方法相比，Siege使用更少的查询，<strong>在GPT-3.5-Turbo上实现了100%的成功率</strong>，在GPT-4上实现了 97% 的成功率。<p class=image-wrapper><img data-img-size-val=1080,1218 src=https://img.36krcdn.com/hsossms/20250319/v2_203f83381c74474e865fb2270cd5224f@5888275_oswg244480oswg1080oswg1218_img_000?x-oss-process=image/format,jpg/interlace,1><p>审稿人评价称，Siege是一种“有效、直观的方法” ，并且告知了人们需要重新评估现有的人工智能防御策略。<h3><strong>预测蛋白质-核酸结合位点</strong></h3><p>除了这两篇之外，还有一篇论文和计算生物学相关，由于完成时已经错过了ICLR会期，转而投稿期刊，目前正在接受审查。<p>这项研究提出了一种名为<strong>EGNN-Fusion</strong>的架构，能够<strong>预测蛋白质-核酸结合位点</strong>。<p>它的性能可与最先进的方法相媲美，同时将参数数量减少了95%，体现了Zochi跨领域迁移知识和解决AI之外的复杂科学挑战的能力。<p>和前面两篇一样，这篇论文也进行了程序自动化评分，得分为7分，所以Zochi三篇论文的平均成绩为7.67。<p class=image-wrapper><img data-img-size-val=1080,894 src=https://img.36krcdn.com/hsossms/20250319/v2_4b4087af3ee640b7b7dfcc7805083617@5888275_oswg143135oswg1080oswg894_img_000?x-oss-process=image/format,jpg/interlace,1><h2><strong>多智能体协作完成科研流程</strong></h2><p>除了能在不到一周的时间内自主写出一篇高质量论文之外，<strong>Zochi还挑战了MLE-Bench的Kaggle子集</strong>。<p>结果在没有任何特定任务优化的情况下，Zochi直接取得了SOTA水准，并且<strong>在80%的任务上超越了人类的平均表现</strong>、在一半的任务当中获得金牌。<p class=image-wrapper><img data-img-size-val=1080,513 src=https://img.36krcdn.com/hsossms/20250319/v2_4781b84d11b746ab985b29f1a6760779@5888275_oswg292810oswg1080oswg513_img_000?x-oss-process=image/format,jpg/interlace,1><p>那么，Zochi是怎么做到的呢？其中的关键，就在于当下流行的<strong>多智能体协作框架</strong>。<p>Zochi将科学方法分解为专门的组件,每个组件处理研究过程中不同的过程，具体包括四个阶段：<p>文献分析和知识综合；<p>假设生成和细化，确定研究方向；<p>实验设计和实施、评估；<p>数据分析和解释以及科学交流。<p>给Zochi设定的研究目标，既可以是一般的研究领域（如“AI安全”），也可以是一个细粒度问题或思路（如“多模态表征对齐方法”）。<p>系统进行广泛的探索和迭代过程，Zochi生成多个候选假设，设计并执行实验来测试这些假设，分析结果，并根据发现迭代优化其方法。<p>最后，Zochi以研究论文的格式起草一份报告，不断完善直到质量足以提交同行评议。<p class=image-wrapper><img data-img-size-val=1080,333 src=https://img.36krcdn.com/hsossms/20250319/v2_7e6efe421dbc4c6caf2e08685baea483@5888275_oswg72012oswg1080oswg333_img_000?x-oss-process=image/format,jpg/interlace,1><p>此外Zochi的另一个关键，是其<strong>结构化验证过程</strong>，类似于学术研究中的导师-学生关系。<p>在研究过程的关键节点，人类专家需要在下一步骤进行之前验证Zochi的工作，具体包括三个关键阶段——大规模实验开始之前、准备文稿之前，以及文稿完成之后。<p>反馈侧重于验证方法的合理性，并验证报告的结果是否准确反映实验结果，以确保完整性。<p>除了强制性验证外，<strong>人类专家还可以选择随时提供高层次的反馈</strong>，这一过程主要用于论文写作，因为Zochi经常难以遵循预期的提交格式（如页面限制）。<p>不过人类输入通常包括几句简短的评论，用于指出潜在问题或建议替代方向，而不是给予详细指示。<h2><strong>“AI科研”仍然争议不断</strong></h2><p>Zochi这次取得的成绩，在AI当中确实是一个不错的水平，但并不是最早的AI科研系统。<p>去年，“Transformer八子”之一的Llion Jones创立的Sakana AI，推出了一个基于AI的自动化科研系统。<p>而且这个系统名字简单粗暴，就叫<strong>AI Scientist</strong>，并且已经有了第二代。<p>也是在这届ICLR上，第二代AI Scientist的论文在其中的一个研讨会上通过了同行评审，分数为6/7/6。<p class=image-wrapper><img data-img-size-val=1080,989 src=https://img.36krcdn.com/hsossms/20250319/v2_774643c5254d4c70bb2b026b5f1487a7@5888275_oswg428588oswg1080oswg989_img_000?x-oss-process=image/format,jpg/interlace,1><p>不过，研讨会和ICLR主会议的录用标准也存在不同，前者的录用率大约是后者的两到三倍。<p>在Sakana内部基于ICLR主会议规则进行的评审中，AI Scientist-v2的论文并未通过。<p>这似乎也和Intology基于NeurIPS规则进行的机器评测结果形成了对应，AI Science v2的平均成绩不到四分，甚至还不如前一代。<p>当然，Zochi的成绩相对高出不少，但最终能不能入选主会议也要等待最终结果。<p class=image-wrapper><img data-img-size-val=1080,894 src=https://img.36krcdn.com/hsossms/20250319/v2_73cc5bb20d2647879eb3f0a06db9dfeb@5888275_oswg148670oswg1080oswg894_img_000?x-oss-process=image/format,jpg/interlace,1><p>但是，由于学术界针对AI科研还存在很大争议，即使成功入围，研究团队可能也会在正式发稿之前撤回。<p>Intology就表示，出于维护学术诚信的考虑，认同AI不应当被列为学术作品的作者，但正在和研讨会组织者进行讨论，决定是否向研究界展示。<p class=image-wrapper><img data-img-size-val=1080,967 src=https://img.36krcdn.com/hsossms/20250319/v2_aae7fdfd79bd4502b173f45510101772@5888275_oswg456878oswg1080oswg967_img_000?x-oss-process=image/format,jpg/interlace,1><p>而在前段时间，另一家顶会CVPR就拒绝了19篇论文，其原因正是和滥用AI有关。<p>甚至CVPR还明确要求，审稿人撰写评审意见同样不能使用AI，也不能把任何实质性内容交给AI（哪怕是用于翻译也不可以）。<p>学术会议之外，国内外诸多高校也开始针对学生论文使用AI的情况加强审查，并出台限制措施。<p>的确在现实情况当中，确有滥用AI的行为存在，颁布这类规定的目的也是基于学术诚信的考量。<p>但一禁了之不应是长久之策，还应该对学术研究从事者，特别是学生群体给予正确引导，并积极探索AI提效与学术不端之间的合理边界。<p>那么，你认为AI在学术活动当中，怎样被利用才是合理的呢？<p class=editor-note>本文来自微信公众号<a rel="noopener noreferrer nofollow"href=https://mp.weixin.qq.com/s/KPGmPw5CCfyUMDv5XK_ziw target=_blank>“量子位”</a>，作者：关注前沿科技，36氪经授权发布。</div></div><div class=common-width><div class=article-footer-txt><p>该文观点仅代表作者本人，36氪平台仅提供信息存储空间服务。</div></div></div></div></div><div class=ad87-box><div><div class=kr-ad-article-detail-817><span class=kr-ad-logo>广告</span><div class=kr-ad-article-detail-817-main><a rel="noopener noreferrer 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