LLMs copy biased analyst ratings in investment decisions but a new detection method encourages independent reasoning and can improve stock return predictions beyond human levels.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=
4 Pith papers cite this work. Polarity classification is still indexing.
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cs.CL 4years
2026 4verdicts
UNVERDICTED 4representative citing papers
OptiVerse is a new benchmark spanning neglected optimization domains that shows LLMs suffer sharp accuracy drops on hard problems due to modeling and logic errors, with a Dual-View Auditor Agent proposed to improve performance.
GoLongRL releases a 23K-sample open long-context RL dataset spanning 9 tasks and introduces TMN-Reweight to improve multitask optimization, achieving performance comparable to much larger models under GRPO.
DCM-Agent improves LLM performance on multi-paradigm optimization problems by 11-21% via dual-cluster memory construction and dynamic inference guidance.
citing papers explorer
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Fin-Bias: Comprehensive Evaluation for LLM Decision-Making under human bias in Finance Domain
LLMs copy biased analyst ratings in investment decisions but a new detection method encourages independent reasoning and can improve stock return predictions beyond human levels.
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OptiVerse: A Comprehensive Benchmark towards Optimization Problem Solving
OptiVerse is a new benchmark spanning neglected optimization domains that shows LLMs suffer sharp accuracy drops on hard problems due to modeling and logic errors, with a Dual-View Auditor Agent proposed to improve performance.
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GoLongRL: Capability-Oriented Long Context Reinforcement Learning with Multitask Alignment
GoLongRL releases a 23K-sample open long-context RL dataset spanning 9 tasks and introduces TMN-Reweight to improve multitask optimization, achieving performance comparable to much larger models under GRPO.
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Dual-Cluster Memory Agent: Resolving Multi-Paradigm Ambiguity in Optimization Problem Solving
DCM-Agent improves LLM performance on multi-paradigm optimization problems by 11-21% via dual-cluster memory construction and dynamic inference guidance.