@ujojicieu202553286

Most web agents summarize or hand back a list of links. Pinpoint returns the one value you asked for (a price, a date, a version, a phone number) together with the page and the exact quote it came from. If it cannot verify the value, it returns an empty answer instead of guessing. How it works: each question starts by writing a valid placeholder JSON, so a crash never breaks the output. The agent fetches the start page and up to 8 same-site links ranked by how well their link text matches the question. It switches to a headless Chromium browser only when a page renders with JavaScript. Pages are cleaned to text with table rows kept, and passages are ranked with BM25. A question classifier decides the expected answer type, and Qwen3-8B, served locally on an AMD Instinct GPU with ROCm, picks a candidate value from the top passages. The answer is accepted only if it appears verbatim in the cited passage and matches the expected type. Otherwise a rule-based extractor is tried, and then an empty answer. The model loads once at container start, and every question runs under a hard deadline. No external API keys are used: all inference runs on the AMD GPU. Results on our open 40-question benchmark across [X] real sites: [X]% exact match, 0 fabricated answers, 8/8 correct empty answers on unanswerable questions, median [X] s per question. The benchmark, eval script and Docker image are open source.

Six Matches. One leaderboard. Build on AMD, earn points and compete for prizes.