Agent skill

Domain Adaptation Papers Guide

by wentorai in wentorai/research-plugins

Comprehensive collection of domain adaptation research papers

Install Domain Adaptation Papers Guide

skills CLI

$ npx skills add wentorai/research-plugins --skill domain-adaptation-papers-guide -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install wentorai/research-plugins domain-adaptation-papers-guide --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/domains/ai-ml/domain-adaptation-papers-guide .claude/skills/domain-adaptation-papers-guide && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "domain-adaptation-papers-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/domains/ai-ml/domain-adaptation-papers-guide into .claude/skills/domain-adaptation-papers-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "domain-adaptation-papers-guide", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/wentorai/research-plugins/tree/main/skills/domains/ai-ml/domain-adaptation-papers-guide

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add wentorai/research-plugins --skill domain-adaptation-papers-guide -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install wentorai/research-plugins domain-adaptation-papers-guide --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/domains/ai-ml/domain-adaptation-papers-guide .agents/skills/domain-adaptation-papers-guide && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "domain-adaptation-papers-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/domains/ai-ml/domain-adaptation-papers-guide into .agents/skills/domain-adaptation-papers-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "domain-adaptation-papers-guide", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add wentorai/research-plugins --skill domain-adaptation-papers-guide -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install wentorai/research-plugins domain-adaptation-papers-guide --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/domains/ai-ml/domain-adaptation-papers-guide .cursor/skills/domain-adaptation-papers-guide && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "domain-adaptation-papers-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/domains/ai-ml/domain-adaptation-papers-guide into .cursor/skills/domain-adaptation-papers-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "domain-adaptation-papers-guide", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/wentorai/research-plugins.git --path skills/domains/ai-ml/domain-adaptation-papers-guide

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add wentorai/research-plugins --skill domain-adaptation-papers-guide -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install wentorai/research-plugins domain-adaptation-papers-guide --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/domains/ai-ml/domain-adaptation-papers-guide .gemini/skills/domain-adaptation-papers-guide && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "domain-adaptation-papers-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/domains/ai-ml/domain-adaptation-papers-guide into .gemini/skills/domain-adaptation-papers-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "domain-adaptation-papers-guide", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install wentorai/research-plugins domain-adaptation-papers-guide

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add wentorai/research-plugins --skill domain-adaptation-papers-guide -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/domains/ai-ml/domain-adaptation-papers-guide .github/skills/domain-adaptation-papers-guide && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "domain-adaptation-papers-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/domains/ai-ml/domain-adaptation-papers-guide into .github/skills/domain-adaptation-papers-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "domain-adaptation-papers-guide", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add wentorai/research-plugins --skill domain-adaptation-papers-guide -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install wentorai/research-plugins domain-adaptation-papers-guide --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/domains/ai-ml/domain-adaptation-papers-guide .opencode/skills/domain-adaptation-papers-guide && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "domain-adaptation-papers-guide" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/domains/ai-ml/domain-adaptation-papers-guide into .opencode/skills/domain-adaptation-papers-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "domain-adaptation-papers-guide", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: domain-adaptation-papers-guide
GitHub stars: 298
Used in: 1 other repo
Token cost: ~1.5k tokens
SKILL.md length: 252 words
Files: 1
Skills in repo: 405
Repo updated: Jun 19, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Comprehensive collection of domain adaptation research papers

Works in 5 steps: Literature survey: Map the DA research… → Method selection: Choose appropriate DA… → Benchmark comparison: Compare methods on… → …
Research & Science work in your project
SKILL.md covers Overview, Taxonomy of Methods, Key Methods by Era and Paper Tracking, plus 5 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Domain Adaptation Papers Guide is an agent skill from wentorai/research-plugins. Comprehensive collection of domain adaptation research papers

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science. The repository describes itself as: 350+ academic research skills, MCP configs, and plugins for Research-Claw and AI agents. The licence is MIT.

When your agent uses it

Research & Science work in your project

Example prompts

“/domain-adaptation-papers-guide”

Requirements

Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

Literature survey: Map the DA research landscape
Method selection: Choose appropriate DA technique for your task
Benchmark comparison: Compare methods on standard datasets
Research gaps: Identify under-explored DA settings
Course material: Teach transfer learning and DA

What it can do on your machine

Read from SKILL.md and the folder at commit bf44b3c. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are python and markdown).
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
- github.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Domain Adaptation Papers Guide loads about 1.5k tokens when it runs. Until then it costs about 23 tokens; SKILL.md has 252 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~23
When it runs · the whole SKILL.md, loaded when a task matches: ~1.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from wentorai/research-plugins at commit bf44b3c, republished under its MIT licence (© wentorai). 252 words, ~1,466 tokens.

Download SKILL.mdSave it as .claude/skills/domain-adaptation-papers-guide/SKILL.md (or your agent's skills folder).

name: domain-adaptation-papers-guide
description: Comprehensive collection of domain adaptation research papers

Domain Adaptation Papers Guide

Overview

Domain adaptation addresses the problem of training models on one data distribution (source domain) and deploying them on a different distribution (target domain). This curated collection covers the full spectrum — from unsupervised domain adaptation (UDA) and domain generalization to partial, open-set, and source-free adaptation. Organized by methodology and application area with regularly updated paper lists.

Taxonomy of Methods

Domain Adaptation
├── Unsupervised DA (UDA)
│   ├── Discrepancy-based (MMD, CORAL, CDD)
│   ├── Adversarial-based (DANN, ADDA, CDAN)
│   ├── Reconstruction-based (DRCN, DSN)
│   └── Self-training (SHOT, CBST)
├── Semi-supervised DA
├── Source-free DA (no source data at adaptation time)
├── Partial DA (target has subset of source classes)
├── Open-set DA (target has unknown classes)
├── Universal DA (no prior on label set relationship)
├── Multi-source DA
├── Domain Generalization (no target data at all)
└── Test-time Adaptation (adapt at inference)

Key Methods by Era

Classical Methods

Method	Year	Approach	Key Idea
TCA	2011	Kernel	Transfer Component Analysis
GFK	2012	Subspace	Geodesic Flow Kernel
SA	2013	Subspace	Subspace Alignment
DAN	2015	MMD	Deep Adaptation Networks
DANN	2016	Adversarial	Domain-Adversarial Neural Networks
ADDA	2017	Adversarial	Adversarial Discriminative DA
CORAL	2016	Statistics	Correlation Alignment

Modern Methods

Method	Year	Approach	Key Idea
CDAN	2018	Adversarial	Conditional adversarial + entropy
MCD	2018	Discrepancy	Maximum Classifier Discrepancy
SHOT	2020	Source-free	Self-supervised pseudo-labeling
TENT	2021	Test-time	Entropy minimization at test time
DAFormer	2022	Transformer	DA for semantic segmentation
PADCLIP	2023	Vision-language	CLIP-based domain adaptation

Paper Tracking

python

import arxiv

def find_da_papers(subtopic="unsupervised", days=30):
    """Find recent domain adaptation papers on arXiv."""
    queries = {
        "unsupervised": "abs:unsupervised domain adaptation",
        "source_free": "abs:source-free domain adaptation",
        "generalization": "abs:domain generalization",
        "test_time": "abs:test-time adaptation OR test-time training",
    }

    search = arxiv.Search(
        query=queries.get(subtopic, queries["unsupervised"]),
        max_results=30,
        sort_by=arxiv.SortCriterion.SubmittedDate,
    )

    for result in search.results():
        print(f"[{result.published.strftime('%Y-%m-%d')}] "
              f"{result.title}")
        print(f"  {result.entry_id}")

find_da_papers("source_free")

Benchmark Datasets

python

# Standard DA benchmarks
benchmarks = {
    "Office-31": {
        "domains": ["Amazon", "DSLR", "Webcam"],
        "classes": 31,
        "task": "Object recognition",
    },
    "Office-Home": {
        "domains": ["Art", "Clipart", "Product", "Real World"],
        "classes": 65,
        "task": "Object recognition",
    },
    "VisDA-2017": {
        "domains": ["Synthetic", "Real"],
        "classes": 12,
        "task": "Large-scale sim-to-real",
    },
    "DomainNet": {
        "domains": ["Clipart", "Infograph", "Painting",
                     "Quickdraw", "Real", "Sketch"],
        "classes": 345,
        "task": "Large-scale multi-domain",
    },
    "PACS": {
        "domains": ["Photo", "Art", "Cartoon", "Sketch"],
        "classes": 7,
        "task": "Domain generalization",
    },
}

for name, info in benchmarks.items():
    print(f"\n{name}: {info['classes']} classes, "
          f"{len(info['domains'])} domains")
    print(f"  Domains: {', '.join(info['domains'])}")

Application Areas

Application	Source → Target Example
Medical imaging	Hospital A → Hospital B scanners
Autonomous driving	Simulation → Real world
Remote sensing	Region A → Region B satellite
NLP	News text → Social media
Speech	Studio → Noisy environments
Robotics	Sim → Real manipulation

Reading Roadmap

markdown

### Beginner Path
1. "A Survey on Transfer Learning" (Pan & Yang, 2010)
2. "Domain Adaptation for Object Recognition" (Saenko et al., 2010)
3. "Deep Domain Confusion" (Tzeng et al., 2014)
4. DANN paper (Ganin et al., 2016)

### Intermediate Path
5. CDAN (Long et al., 2018)
6. MCD (Saito et al., 2018)
7. "Moment Matching for Multi-Source DA" (Peng et al., 2019)

### Advanced Path
8. SHOT (Liang et al., 2020) — source-free
9. TENT (Wang et al., 2021) — test-time
10. "Benchmarking DA on Language" (Ramponi & Plank, 2020)

Use Cases

Literature survey: Map the DA research landscape
Method selection: Choose appropriate DA technique for your task
Benchmark comparison: Compare methods on standard datasets
Research gaps: Identify under-explored DA settings
Course material: Teach transfer learning and DA

References

Files

Just SKILL.md in skills/domains/ai-ml/domain-adaptation-papers-guide of wentorai/research-plugins.

Open the folder on GitHubat commit bf44b3c

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in wentorai/research-plugins, which our catalogue first saw on October 7, 2026.

brycewang-stanford/Auto-Empirical-Research-Skillsskills/43-wentorai-research-plugins/skills/domains/ai-ml/domain-adaptation-papers-guide

Compare with similar skills

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Questions about Domain Adaptation Papers Guide

What does Domain Adaptation Papers Guide do?

Comprehensive collection of domain adaptation research papers. Domain Adaptation Papers Guide is an agent skill from wentorai/research-plugins.

When should I use Domain Adaptation Papers Guide?

Domain Adaptation Papers Guide fits situations like: research & Science work in your project.

How do I install Domain Adaptation Papers Guide in Claude Code?

Run `npx skills add wentorai/research-plugins --skill domain-adaptation-papers-guide -a claude-code`. Or copy the skill folder (skills/domains/ai-ml/domain-adaptation-papers-guide in wentorai/research-plugins) into .claude/skills/domain-adaptation-papers-guide in your project. Claude Code loads it when a task matches its description.

How do I install Domain Adaptation Papers Guide in Codex?

Run `npx skills add wentorai/research-plugins --skill domain-adaptation-papers-guide -a codex`. Or copy the skill folder (skills/domains/ai-ml/domain-adaptation-papers-guide in wentorai/research-plugins) into .agents/skills/domain-adaptation-papers-guide in your project. Codex loads it when a task matches its description.

Can I use Domain Adaptation Papers Guide in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add wentorai/research-plugins --skill domain-adaptation-papers-guide -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/domain-adaptation-papers-guide, .gemini/skills/domain-adaptation-papers-guide, .github/skills/domain-adaptation-papers-guide and .opencode/skills/domain-adaptation-papers-guide in your project.

What does Domain Adaptation Papers Guide need to run?

SKILL.md names no scripts, command-line tools or credentials: Domain Adaptation Papers Guide is instructions for the agent only. Our summary lists: Python 3.

Does Domain Adaptation Papers Guide access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Domain Adaptation Papers Guide safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Domain Adaptation Papers Guide use?

Domain Adaptation Papers Guide is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Domain Adaptation Papers Guide use?

About 1.5k tokens (SKILL.md is roughly 5.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Domain Adaptation Papers Guide?

Skills that share tags, products or a category with Domain Adaptation Papers Guide: Hypothesis Generation (spacering-net/codeg, 3.9k stars), GitHub Deep Research (bytedance/deer-flow, 84k stars), Nature Paper Card (Yuan1z0825/nature-skills, 47k stars) and Content Research Writer (weapp-tailwindcss/weapp-tailwindcss, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Domain Adaptation Papers Guide?

wentorai (a GitHub user) maintains it in wentorai/research-plugins, which has 298 GitHub stars. The repository holds 405 skills in this directory. The repository was last updated on June 19, 2026.

Source: wentorai/research-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Domain Adaptation Papers Guide

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Domain Adaptation Papers Guide

Overview

Taxonomy of Methods

Key Methods by Era

Classical Methods

Modern Methods

Paper Tracking

Benchmark Datasets

Application Areas

Reading Roadmap

Use Cases

References

Files

Used in 1 other repository

Compare with similar skills

Similar skills

More from wentorai/research-plugins

Related

Questions about Domain Adaptation Papers Guide