arXiv AI
Jun 3
Merit or networks? What decides where research is published
arXiv:2606. 03763v1 Announce Type: cross Abstract: Does scientific publishing reward the quality of ideas or the advantage of connections?
Merit or networks? What decides where research is published
Does scientific publishing reward the quality of ideas or the advantage of connections? The question is universal to prestige-driven science, yet it has resisted decades of study because a paper's quality could not be gauged ahead of its publication fate without using that fate as the yardstick.
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arXiv AI
Jun 9
Contemporary AI lacks the imagination to diverge or negate in science
arXiv:2606. 08251v1 Announce Type: cross Abstract: Bold projections that artificial intelligence will accelerate scientific discovery have raced ahead of evidence from working scientists, and the field still lacks large-scale, scientist-in-the-loop tests of these claims.
arXiv AI
Sep 23
Social Influence and the Allocation of Scientific Attention in AI Populations
arXiv:2609.22408v1 Announce Type: new Abstract: AI systems are becoming participants in the evaluation and use of scientific research. They encounter citation counts, download statistics and lists of...
arXiv AI
Jun 10
Gaming AI-Assisted Peer Reviews Poses New Risks to the Scientific Community
arXiv:2606. 10159v1 Announce Type: cross Abstract: AI is increasingly used to support scientific peer review, from manuscript screening, reviewer assistance to editorial triage.
arXiv AI
2d ago
Science Utopia? Closed-Loop LLM Simulation of Academic Research Ecosystems
The paper introduces SciUtopia, a closed‑loop large‑language‑model simulation framework that models the evolving academic research ecosystem, including research direction, collaboration, publication, peer review, funding, and researcher attrition. Running 61 simulation worlds, the system simulates over 40,000 researchers and 1.2 million LLM‑generated peer reviews, revealing that rejection‑driven resubmission increases reviewer burden, cautious exploration balances citation impact with career success, and resource inequality can arise without early‑funding advantage.
arXiv AI
Jun 4
Knowledge Index of Noah's Ark
arXiv:2606. 05104v1 Announce Type: new Abstract: Knowledge benchmarks for LLMs face three issues: scaling-driven designs that do not operationalize disciplinary representativeness; flat-payment annotation that permits lazy consensus; and unaudited ranking instability under bounded test budgets.
Hugging Face Trending Papers
Aug 10
How Can Rhetoric Reward-Hack AI Reviewers? Dissecting Rhetorical Sensitivity in AI-Based Peer Review
As large language models increasingly participate in scientific evaluation, we investigate a potential form of reward hacking: how rhetorical choices shape AI-review judgments when reported scientific content is preserved and how these effects vary across evaluation conditions. We construct a controlled corpus of 4,200 full-paper manuscripts derived from 120 anonymized ICLR 2026 submissions.
arXiv AI
Sep 25
Generating Interesting Scientific Ideas using Knowledge Graphs and LLMs: Evaluations with 100 Research Group Leaders
The paper introduces SciMuse, an AI system that generates personalized research ideas by combining a knowledge graph of 58 million papers with a large language model. A large-scale evaluation involving over 100 research group leaders across disciplines rated more than 4,400 ideas, yielding modest overall interest scores but showing that 24.9% were rated highly. The study also demonstrates that graph-derived features can predict idea interest and can be used to control idea properties, offering a new methodology for generating and assessing scientific ideas.
arXiv AI
Aug 11
How Can Rhetoric Reward-Hack AI Reviewers? Dissecting Rhetorical Sensitivity in AI-Based Peer Review
arXiv:2608. 08975v1 Announce Type: cross Abstract: As large language models increasingly participate in scientific evaluation, we investigate a potential form of reward hacking: how rhetorical choices shape AI-review judgments when reported scientific content is preserved and how these effects vary across evaluation conditions.
arXiv Computation and Language
Sep 1
PaperGym: Rubric-Centered Evolution for Research-Plan Generation
PaperGym is a framework that transforms each research paper into a training environment for AI research planning, using rubrics extracted from the paper’s method and experiments as a critic. It synthesizes research questions from the goal and background, and derives evaluation criteria from the method and experiments, reducing criterion leakage to 3.7%. Experiments with Qwen models show that training with PaperGym’s rubric improves benchmark performance by up to 5.6 points and outperforms existing datasets and fine‑tuning baselines.
arXiv AI
Jul 15
The Model Knows Your Project, Not You: Measuring Recognition in LLMs with NameRank
arXiv:2607. 12520v1 Announce Type: new Abstract: What a frontier model recalls about a person or tool from its own weights -- before any retrieval step -- often shapes the first description a human sees, making that parametric corpus presence a measurement problem.
arXiv AI
Sep 15
Positioning manuscripts in the scientific landscape with agentic AI
arXiv:2609.13760v1 Announce Type: new Abstract: Publishing a research manuscript is a routine yet demanding part of scientific life: time-consuming, stressful, and often uncertain in outcome. Recent...