activity
20242026
collaborators

13 papers

cs.CL2026

PaperMentor: A Human-Centered Multi-Agent Writing Tutor for AI Research Papers on Overleaf

Jiarui Liu, Terry Jingchen Zhang, Ryan Faulkner +17

Expert writing feedback from experienced researchers is critical for early-career scholars to improve their manuscripts, yet high-quality feedback often remains scarce because revi…

cs.AI2026

Learning to Reason Efficiently with A* Post-Training

Andreas Opedal, Francesco Ignazio Re, Abulhair Saparov +3

Many applications of large language models (LLMs) require deductive reasoning, yet models frequently produce incorrect or redundant inference steps. We frame natural language infer…

cs.AI2026

Test of Time: Rethinking Temporal Signal of Benchmark Contamination

Terry Jingchen Zhang, Gopal Dev, Ning Wang +8

Post-cutoff performance decay of LLMs has been widely interpreted as a temporal signal for benchmark contamination, where public information released before the training cutoff may…

cs.CY2026

Preserving Historical Truth: Detecting Historical Revisionism in Large Language Models

Francesco Ortu, Joeun Yook, Punya Syon Pandey +5

Large language models (LLMs) are increasingly used as sources of historical information, motivating the need for scalable audits on contested events and politically charged narrati…

cs.LG2026

LoRA and Privacy: When Random Projections Help (and When They Don't)

Yaxi Hu, Johanna Düngler, Bernhard Schölkopf +1

We introduce the (Wishart) projection mechanism, a randomized map of the form with and study its differential privacy properties. For ve…

cs.CL2026

Are Language Models Efficient Reasoners? A Perspective from Logic Programming

Andreas Opedal, Yanick Zengaffinen, Haruki Shirakami +5

Modern language models (LMs) exhibit strong deductive reasoning capabilities, yet standard evaluations emphasize correctness while overlooking a key aspect of reasoning: efficiency…