lihanc111

4 ms·

1.
by lihanc111 7mo ago
Yeah surprisingly the text of this blog is almost entirely generated by AI :) I gave all the ideas though
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by lihanc111 7mo ago
Actually not, i think the --- was just mistakenly typed XD
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We Analyzed 413K Agent Runs. Here's What Separates the Ones That Succeed(twitter.com)
2 points by lihanc111 7mo ago|5 comments
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by lihanc111 7mo ago
Hey HN, We dug into 17 billion tokens of behavioral data across 413K AI agent trajectories (CoderForge-Preview) attempting real GitHub issues. Instead of just looking at final SWE-bench scores, we compared successful runs against failing ru
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Evaluating Evolving Agents with Evolving Benchmarks(frontier-cs.org)
3 points by lihanc111 7mo ago|1 comments
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by lihanc111 7mo ago
Evolving agent systems (agents that use continual learning, memory, or context refinement) are becoming the mainstream. However, up until now, most papers show gains on only about 10 tasks, or small subsets of existing benchmarks. The bigge
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FrontierCS Benchmark(frontier-cs.org)
1 points by lihanc111 8mo ago|1 comments
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by lihanc111 8mo ago
We created a benchmark for open-ended computer science problems including algorithmic problems handpicked by former IOI gold medalists and research problems in various areas by PhD students. Read more in the blog and leaderboard for how fro
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Reuse non-prefix KV Cache and speed up RAG by 3X with LMCache(github.com)
5 points by lihanc111 1y ago|1 comments
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by lihanc111 1y ago
Hey HN Community! A while back, we shared our open-source project LMCache here and were blown away by the incredible support and feedback. Today, our team is thrilled to share more about one of our core components: CacheBlend. Recognized wi
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by lihanc111 1y ago
Please send to contact@lmcache.ai
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by lihanc111 1y ago
It is almost true for both. Although for the second case you can just skip storing in these cases where there is little improvement.
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by lihanc111 1y ago
It is in IBM's llm-d open source stack
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Lossless LLM 3x Throughput Increase by LMCache(github.com)
154 points by lihanc111 1y ago|53 comments
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by lihanc111 1y ago
Our team has built this open source project, LMCache, to reduce repetitive computation in LLM inference and make systems serve more people (3x more throughput in chat applications) and it has been used in IBM's open source LLM inferenc