Comparison
Instruction-Tuning-Papers vs LLM-Agent-Paper-List
Verdict
Pick Instruction-Tuning-Papers if instruction-Tuning-Papers is a curated reading list focused on the instruction-tuning domain for language models; pick LLM-Agent-Paper-List if lists essential papers on LLM-based agents with integrated tools like AgentGym for RL training.
Markdown twin · Instruction-Tuning-Papers alternatives · LLM-Agent-Paper-List alternatives
GraphCanon updated 2d
vs
Trust & integrity
| Signal | Instruction-Tuning-Papers | LLM-Agent-Paper-List |
|---|---|---|
| Maintenance | Dormant (1113d since push) As of 1w · github_public_v1 | Slowing (339d since push) As of 2d · github_public_v1 |
| Provenance | Not a fork · Personal account As of 1w · github_public_v1 | Not a fork · Personal account As of 2d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- Instruction-Tuning-Papers
- Reading list of Instruction-tuning papers.
- LLM-Agent-Paper-List
- Must-read papers for LLM-based agents.
Stars
- Instruction-Tuning-Papers
- 768
- LLM-Agent-Paper-List
- 8.2k
Forks
- Instruction-Tuning-Papers
- 23
- LLM-Agent-Paper-List
- 495
Open issues
- Instruction-Tuning-Papers
- 0
- LLM-Agent-Paper-List
- 31
Language
- Instruction-Tuning-Papers
- -
- LLM-Agent-Paper-List
- -
Adopt for
- Instruction-Tuning-Papers
- Instruction-Tuning-Papers is a curated reading list focused on the instruction-tuning domain for language models.
- LLM-Agent-Paper-List
- Lists essential papers on LLM-based agents with integrated tools like AgentGym for RL training.
Persona
- Instruction-Tuning-Papers
- -
- LLM-Agent-Paper-List
- -
Runtime
- Instruction-Tuning-Papers
- -
- LLM-Agent-Paper-List
- -
License
- Instruction-Tuning-Papers
- -
- LLM-Agent-Paper-List
- -
Last pushed
- Instruction-Tuning-Papers
- Jul 20, 2023
- LLM-Agent-Paper-List
- Sep 12, 2025
Categories
- Instruction-Tuning-Papers
- Model Training
- LLM-Agent-Paper-List
- AI Agents, Evaluation & Observability
Trust and health
Maintenance
- Instruction-Tuning-Papers
- Dormant (18%)
- LLM-Agent-Paper-List
- Slowing (36%)
Days since push
- Instruction-Tuning-Papers
- 1113d
- LLM-Agent-Paper-List
- 339d
Open issues (now)
- Instruction-Tuning-Papers
- 0
- LLM-Agent-Paper-List
- 31
Stars delta
- Instruction-Tuning-Papers
- Unknown
- LLM-Agent-Paper-List
- +4 (30d)
Open issues delta
- Instruction-Tuning-Papers
- Unknown
- LLM-Agent-Paper-List
- +2 (30d)
Full report
- Instruction-Tuning-Papers
- Trust report
- LLM-Agent-Paper-List
- Trust report
Choose Instruction-Tuning-Papers if…
- Tags unique to Instruction-Tuning-Papers: cross-task-generalization, instruction-tuning, multi-task learning, natural-language-processing.
- Also covers Model Training.
- When you're looking to enhance your understanding of how natural language instructions can empower language models in diverse tasks.
When NOT to use Instruction-Tuning-Papers
- Avoid this resource if you are looking for tools or frameworks to implement instruction tuning rather than theoretical understanding.
- Not suitable for users in need of a broader overview beyond specific academic papers on language model training methodologies.
- If your interest lies more in general NLP resources or comprehensive toolkits, Instruction-Tuning-Papers may not cover all aspects.
Choose LLM-Agent-Paper-List if…
- Tags unique to LLM-Agent-Paper-List: agent, llm, nlp, rl.
- Also covers AI Agents, Evaluation & Observability.
- Looking to survey key advancements in LLM-based agent research, specifically through papers endorsed by authors.
When NOT to use LLM-Agent-Paper-List
- Seeking real-time interactive debugging tools; focuses more on paper reviews and general frameworks than coding sandbox features.
- Require support documentation in languages other than English or project-specific code details, as licensing and detailed documentation are currently unverified.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (SinclairCoder/Instruction-Tuning-Papers) · observed Aug 6, 2026
- GitHub forks (SinclairCoder/Instruction-Tuning-Papers) · observed Aug 6, 2026
- Last push (SinclairCoder/Instruction-Tuning-Papers) · observed Jul 20, 2023
- License file (unknown) · observed Aug 6, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (WooooDyy/LLM-Agent-Paper-List) · observed Aug 17, 2026
- GitHub forks (WooooDyy/LLM-Agent-Paper-List) · observed Aug 17, 2026
- Last push (WooooDyy/LLM-Agent-Paper-List) · observed Sep 12, 2025
- License file (unknown) · observed Aug 17, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: Instruction-Tuning-Papers 768 · LLM-Agent-Paper-List 8.2k (synced Aug 6, 2026).
Common questions
- What is the difference between Instruction-Tuning-Papers and LLM-Agent-Paper-List?
- Instruction-Tuning-Papers: Reading list of Instruction-tuning papers.. LLM-Agent-Paper-List: Must-read papers for LLM-based agents.. See the comparison table for live GitHub stats and shared categories.
- When should I choose Instruction-Tuning-Papers over LLM-Agent-Paper-List?
- Choose Instruction-Tuning-Papers over LLM-Agent-Paper-List when Tags unique to Instruction-Tuning-Papers: cross-task-generalization, instruction-tuning, multi-task learning, natural-language-processing; Also covers Model Training; When you're looking to enhance your understanding of how natural language instructions can empower language models in diverse tasks.
- When should I choose LLM-Agent-Paper-List over Instruction-Tuning-Papers?
- Choose LLM-Agent-Paper-List over Instruction-Tuning-Papers when Tags unique to LLM-Agent-Paper-List: agent, llm, nlp, rl; Also covers AI Agents, Evaluation & Observability; Looking to survey key advancements in LLM-based agent research, specifically through papers endorsed by authors.
- When should I avoid Instruction-Tuning-Papers?
- Avoid this resource if you are looking for tools or frameworks to implement instruction tuning rather than theoretical understanding. Not suitable for users in need of a broader overview beyond specific academic papers on language model training methodologies. If your interest lies more in general NLP resources or comprehensive toolkits, Instruction-Tuning-Papers may not cover all aspects.
- When should I avoid LLM-Agent-Paper-List?
- Seeking real-time interactive debugging tools; focuses more on paper reviews and general frameworks than coding sandbox features. Require support documentation in languages other than English or project-specific code details, as licensing and detailed documentation are currently unverified.
- Is Instruction-Tuning-Papers or LLM-Agent-Paper-List more popular on GitHub?
- LLM-Agent-Paper-List has more GitHub stars (8,172 vs 768). Stars measure visibility, not whether either tool fits your constraints.
- Are Instruction-Tuning-Papers and LLM-Agent-Paper-List open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to Instruction-Tuning-Papers or LLM-Agent-Paper-List?
- GraphCanon lists graph-backed alternatives at Instruction-Tuning-Papers alternatives and LLM-Agent-Paper-List alternatives (Instruction-Tuning-Papers markdown twin, LLM-Agent-Paper-List markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, Instruction-Tuning-Papers or LLM-Agent-Paper-List?
- Instruction-Tuning-Papers: Dormant. LLM-Agent-Paper-List: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for Instruction-Tuning-Papers and LLM-Agent-Paper-List?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Instruction-Tuning-Papers trust report; LLM-Agent-Paper-List trust report.