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cs.LG2026
Self-Improving Tabular Language Models via Iterative Reward-Guided Post-Training
Yunbo Long, Tejumade Afonja, Guangya Hao +2
Tabular language models can generate synthetic tables by modeling rows as token sequences, but they are typically trained once with supervised fine-tuning and then used as static s…
cs.AI2026
VeriTrace: Evolving Mental Models for Deep Research Agents
Haolang Zhao, Yunbo Long, Lukas Beckenbauer +1
Deep research agents face vast, interdependent, and pervasively uncertain information. Existing systems explore what evolving intermediate representations should look like, but lea…