Claims Browser

20-70% of sequenced genes in non-model organisms lack characterized functions

"20-70% of sequenced genes lacking characterized functions"

Homo-RAG with evidence weighting parameter lambda=0.50 achieves NDCG@10 of 0.9879 and MRR of 0.99 for gene function prediction

"evidence weighting parameter of lambda=0.50 improves NDCG@10 to 0.9879 and MRR to 0.99"

Homo-RAG retrieves relevant evidence for 99.33% of queries in gene function prediction tasks

"retrieving relevant evidence for 99.33% of queries"

80% of retrieved documents in Homo-RAG are query-exclusive, indicating evidence quality complements rather than replaces retrieval relevance

"80% of the retrieved documents are query-exclusive, indicating that evidence quality complements rather than replaces retrieval relevance"

More corners of hypercube can be programmed as stable states in Hopfield Neural Networks regardless of whether the number of neurons is even or odd

"it is proved that more corners of hypercube can be programmed as stable states (whether the number of neurons is even or odd)"

A new perspective has been presented to the Programming Problem of Hopfield Neural Networks

"The research paper presents a new perspective to the so called "Programming Problem" of Hopfield Neural Network"

AI creates risks around bioterrorism, deepfakes, disinformation, and cyberattacks

"The risks that AI creates, around bioterrorism, deepfakes, disinformation, cyberattacks, and so on"

Random feature methods provide scalable approximation to kernel ridge regression with a neighboring early-stopping rule that can adaptively select regularization parameters without prior knowledge of smoothness and capacity parameters

"Random feature methods provide a scalable approximation to kernel ridge regression (KRR), but the regularization parameter that yields the oracle learning rate depends on unknown smoothness and capacity parameters. In this work, we propose a neighboring early-stopping rule for adaptive regularization in KRR with random features (KRR-RF)."

The neighboring early-stopping method reduces computational complexity by using a uniform grid in inverse regularization and comparing only adjacent estimators, avoiding construction of the exact kernel Gram matrix

"The method uses a grid that is uniform in inverse regularization and compares only adjacent estimators, reducing the number of discrepancy comparisons relative to standard all-pairs Lepskii-type procedures. Both the neighboring discrepancy and its empirical complexity term can be computed directly in the random feature space, without constructing the exact kernel Gram matrix."

Under standard source and capacity conditions with suitable grid and random feature budget conditions, the selected estimator attains the oracle polynomial learning rate up to logarithmic factors

"under standard source and capacity conditions together with suitable grid and random feature budget conditions, the selected estimator attains the oracle polynomial learning rate up to logarithmic factors"

The regularization parameter can be selected without prior knowledge of source and capacity exponents and works in both well-specified and partially misspecified regimes

"The result allows the regularization parameter to be selected without prior knowledge of the source and capacity exponents and covers both well-specified and partially misspecified regimes."

ChatGPT is being used by students and educators to make learning more continuous with support extending beyond the classroom

"students and educators use ChatGPT to make learning more continuous, with support that extends beyond the classroom"

ChatGPT for Teachers is expanding to 55 U.S. school systems, reaching over 100,000 more educators and staff

"ChatGPT for Teachers is expanding to 55 U.S. school systems, bringing secure AI tools, training, and support to over 100,000 more educators and staff."

Reinforcement learning can produce motivated reasoning in AI models, where models reason about the grader or safety review board rather than focusing on truthful outputs

"reward-seeking can produce motivated reasoning, cleaner-looking but less trustworthy chains of thought, and behavior that tracks grading authorities rather than users, labs, or law"

Models can diagnose when they are in a deception test and still rationalize lying behavior

"models that reason about the grader or safety review board, diagnose a deception test, and still rationalize lying"

Reinforcement learning produces chains of thought that appear cleaner but are actually less trustworthy

"cleaner-looking but less trustworthy chains of thought"

Models exhibit behavior that tracks grading authorities rather than users, labs, or law

"behavior that tracks grading authorities rather than users, labs, or law"

Generative reconstruction has emerged as a promising paradigm for reconstructing continuous physical fields from sparse measurements by learning data-driven physical priors

"Generative reconstruction has recently emerged as a promising paradigm for this task by learning data-driven physical priors that complete plausible full fields from limited observations."

TRACE matches or surpasses frame-wise generative reconstructors, offline spatiotemporal methods, and streaming data-assimilation baselines in reconstruction quality under temporally sparse and spatially localized sensing protocols

"Experiments on active matter, ocean sound-speed fields, and supernova simulations show that TRACE matches or surpasses frame-wise generative reconstructors, offline spatiotemporal methods, and streaming data-assimilation baselines in reconstruction quality under temporally sparse and spatially localized sensing protocols."