Excited to introduce our new work ContextBench, designed to evaluate coding agentsโ ability to retrieve the right context from large codebases during SE task resolution process!!
We just released ContextBench ๐
A benchmark built to answer a question many repo-level evaluations still miss:
Do coding agents truly retrieve and use the right context, or do they just get lucky?๐โจ
๐ Highlights
๐งฉ 1,136 real-world issues across 66 repos and 8 languages
๐ง Expert verified gold contexts at file, block, and line levels
๐ฃ Full trajectory tracking of what the agent actually reads and explores
๐ Metrics covering Recall, Precision, F1, Efficiency, and Usage Drop
๐ Key Findings
1๏ธโฃ Complex agentic scaffolds do not improve context retrieval quality ๐
In many cases, they introduce over-engineering, echoing "The Bitter Lesson" in AI research
2๏ธโฃ Many SOTA LLMs favor high recall over precision ๐
They retrieve more context, but also much more noise
3๏ธโฃ Retrieved does not mean utilized โ
Agents often inspect the right code but fail to incorporate it into the final patch
4๏ธโฃ Retrieval strategies that are more balanced tend to achieve stronger Pass@1 while keeping compute cost reasonable โ๏ธโจ
๐ Homepage ๐ https://t.co/4upNH9XDYi
๐ Paper ๐ https://t.co/xXPziAFins
๐ป Code ๐ https://t.co/belNHEFfyi
๐๏ธ Dataset ๐ https://t.co/XaljqOdg4r
Excited to share that I will join NUS (@NUSComputing) as an Assistant Professor this Aug! ๐
Iโm recruiting Ph.D./RAs/interns interested in Program Analysis, Code LLMs, and Agents. ๐ฅ
Self-motivated students with strong backgrounds are especially welcome.
Excited to share that I will join NUS (@NUSComputing) as an Assistant Professor this Aug! ๐
Iโm recruiting Ph.D./RAs/interns interested in Program Analysis, Code LLMs, and Agents. ๐ฅ
Self-motivated students with strong backgrounds are especially welcome.
Excited to share that Iโve recently joined the School of Software at Tsinghua University as an Assistant Professor. Looking forward to the journey ahead! ๐ป๐
Our AI coding model Prometheus, co-developed with Professor He Ye @ye_he_ye, @ucl SSE Team and @Euni_AI, has surpassed @Google's newly released Gemini 3 Pro Preview @geminiapp and achieved Top 5 globally among independent models on SWE-Bench.
- Prometheus GitHub: https://t.co/NqPgz5cKBg
- SWE-Bench results: https://t.co/8SNgZ78PUK (select "Open Scaffold + All Tags")
Stay tuned.
Weโre excited to announce our partnership with @The_Delysium โ together, weโre setting open, autonomous, multilingual, and cost-efficient standards for AI coding.
By bridging AI systems engineering with Web3 best practices โ @LucyOSAI and the YKILY Network โ we aim to make AI development more transparent, verifiable, and accessible for everyone.
Thrilled to announce that I'll be joining UIUC CS @siebelschool as an Assistant Professor in Spring 2026!
๐ข Iโm looking for Fall '26 PhD students who are interested in the intersection of Software Engineering and AI, especially in LLM4Code and Code Agents. Please drop me an email if you are interested in working with me.
Great vibes at #GraphSummit London ๐
Learned a ton + made great memories by Big Ben โจ
@Euni_AI, we share a vision with the graph community:
๐ LLMs need a better way to understand codebases โ knowledge graphs stand between them.
Excited for whatโs ahead! ๐
#AI#Neo4j
๐ New milestone: Hermes hits 50% resolve rate on Terminal-Bench!
๐ Performance:
โ 91.67% easy
โก 54.55% medium
๐ฅ 20.83% hard
Now ranked #6 on the leaderboard, Hermes proves the power of iterative AI agents in complex terminal environments.
#LLM#Agents#AIResearch
Attending OOPSLA/ICFP 2025 in Singapore? ๐โ๏ธ
JOIN us on October 15th, we warmly welcome you to join the Workshop on Language Models for Programming Languages (LMPL) co-hosted at SPLASH 2025 !
๐https://t.co/yTUWj1AglA
๐ฅThis year we are excited to have accepted 22 papers! ๐ฅณ
Prompting is the new programming, but NL suffers from ambiguity. SpecFix (ASE'25) is the first to automatically repair ambiguous programming problem descriptions, resulting in โ Pass@k, and its repairs generalizing across models.
https://t.co/ZPgBIqBr4a
https://t.co/1dqNqD1WRj
๐ Benchmark update ๐
Prometheus + DeepSeek-Chat reached 35.33% resolve rate on SWE-bench Lite โ achieving state-of-the-art performance in autonomous code agents.
This is just the beginning ๐
๐ง Athena Memory System Launched! ๐ง
An innovative memory system purpose-built for autonomous code agents:
โก๏ธ Long-term learning & memory
โก๏ธ Deeper context retention
โก๏ธ Greater adaptability
Athena marks the next leap toward truly self-managing, intelligent code agents.
๐ง Prometheus keeps evolving.
With new integrations & features, weโre pushing the boundaries of what code agents can do:
โขContext-rich problem solving
โขFlexible workflows
โขReal-world performance breakthroughs
๐ Prometheus Major Update ๐
Big leap for autonomous code agents:
๐ MCP Integration for stronger context & multimodal interaction
๐ง Web Search + Custom Build Commands
๐ 44% solve rate on SWE-bench Verified
The future of self-managing code starts now.