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Bo-Yu Yang

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#artificial intelligence Preprint Oct 2026

REVEAL: Reverse Engineering Agentic Latents from Frontier-Model Traces

Frontier LLM agents perform complex interactive tasks, but their inference costs motivate transferring their experience to smaller open-source agents. Distillation and latent communication typically require target-model training or access to source-model internals. We study how textual frontier-model trajectories can p...

Yue-Tian Du, Meng Wang, Yu-Cheng Wang et al. · 0 citations
Jul 2026

Are the Financial Reasoning from LLMs Credible? A Real World Test over Long-Horizon Statements

FinIndices is a large-scale benchmark evaluating data-processing fidelity over uncropped financial statements (up to 32K tokens) and yields substantial zero-hint gains, validating that structured logic can be partially restored via data-centric alignment.

Xin Tong, Xuanming Zhang, Tian-Yi Tang et al. · 0 citations
Jul 2026

Before the Action: Benchmarking LLMs on Prospective Hypothesis Discovery

Results support treating PHD as a distinct target for evaluating how LLMs formulate investigative directions when final conclusions are withheld, with gains for several lower-performing models on HypoArena but regressions for other systems, including a top-performing model.

Tianyun Zhong, Wangyi Jiang, Wei Wang et al. · 0 citations
#artificial intelligence Preprint Aug 2026

The Illusion of $\textit{What If}$: Evaluating the Breakdown of Counterfactual Reasoning in LLMs

A diagnostic benchmark for open-domain, open-form, long-horizon counterfactual causal reasoning, containing 220 what-if questions across STEM, HSS, and Hybrid scenarios, and finds that WhatIfBench remains far from saturated: even the strongest model reaches only a 64.62% final score.

Yu-Cheng Wang, Yuetian Du, Zheng Liu et al. · 0 citations
Jul 2026

Living-Harness Is an Interactive-Agent Evolver

Living-Harness is proposed, a self-evolving agent harness that converts each completed trajectory and its evaluator signals into posterior evidence for bounded harness updates, and supports retrieval-only reuse of the evolved harness state across model backbones.

Yuetian Du, Yucheng Wang, Helsing Xu et al. · 2 citations

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