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DTSTART:20261101T010000
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DESCRIPTION:This talk explores a surprising finding in reinforcement learning for mathematical reasoning: certain language models can achieve substantial performance gains even when trained with completely uninformative or incorrect reward signals. Through extensive experiments on mathematical benchmarks\, we demonstrate that Qwen2.5-Math models improve significantly when trained with random rewards\, format-only rewards\, or even rewards that explicitly favor incorrect answers.\n\nStella a second year Ph.D. student in the Allen School of Computer Science and Engineering at the University of Washington\, advised by Yulia Tsvetkov.\n\nStella received her B.S. and M.S.E. at Johns Hopkins with majors in Computer Science\, Cognitive Science (linguistics focus)\, and Applied Mathematics (statistics focus). I worked as a research assistant at the Center for Language and Speech Processing advised by Philipp Koehn and Kenton Murray.\n\n------\n\nPowered by addevent.com \nShare your next event with us!\n
X-ALT-DESC;FMTTYPE=text/html:This talk explores a surprising finding in reinforcement learning for mathematical reasoning: certain language models can achieve substantial performance gains even when trained with completely uninformative or incorrect reward signals. Through extensive experiments on mathematical benchmarks, we demonstrate that Qwen2.5-Math models improve significantly when trained with random rewards, format-only rewards, or even rewards that explicitly favor incorrect answers.<br><br>Stella a second year Ph.D. student in the Allen School of Computer Science and Engineering at the University of Washington, advised by Yulia Tsvetkov.<br><br>Stella received her B.S. and M.S.E. at Johns Hopkins with majors in Computer Science, Cognitive Science (linguistics focus), and Applied Mathematics (statistics focus). I worked as a research assistant at the Center for Language and Speech Processing advised by Philipp Koehn and Kenton Murray.<br /><br />------<br /><br />Powered by addevent.com <br>Share your next event with us!<br>
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SUMMARY:Stella Li - Spurious Rewards: Rethinking Training Signals in RLVR (Geo Asia)
DTSTART;TZID=America/Los_Angeles:20250611T090000
DTEND;TZID=America/Los_Angeles:20250611T100000
DTSTAMP:20260808T060643Z
TRANSP:OPAQUE
STATUS:CONFIRMED
SEQUENCE:0
LOCATION:https://meet.google.com/yhv-tiir-ava?hs=122&authuser=0
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