defect_zero_iff_one

"MIRIX consists of six distinct, carefully structured memory types: Core, Episodic, Semantic, Procedural, Resource Memory, and Knowledge Vault, coupled with a multi-agent framework that dynamically controls and coordinates updates and retrieval."

"TTRL boosts the pass@1 performance of Qwen-2.5-Math-7B by approximately 211% on the AIME 2024 with only unlabeled test data. Furthermore, although TTRL is only supervised by the maj@n metric, TTRL has demonstrated performance to consistently surpass the upper limit of the initial model maj@n."

"Theoretically, we prove that the global optimum to the training objective function of our method is achieved only when the LLM policy aligns with the target data distribution."

"This cost exhibits reciprocity J(x)=J(x⁻¹), vanishes only at x=1, and diverges at boundary regimes x→0⁺ and x→∞"

"we introduce OpenVid-1M, a precise high-quality dataset with expressive captions... propose a novel Multi-modal Video Diffusion Transformer (MVDiT) capable of mining both structure information from visual tokens and semantic information from text tokens"

"We introduce the concept of pixel-space reasoning... VLMs are equipped with a suite of visual reasoning operations, such as zoom-in and select-frame... a reinforcement learning (RL) phase leverages a curiosity-driven reward scheme to balance exploration between pixel-space reasoning and textual reasoning."

"The benchmark includes a diverse set of 110 explicitly malicious agent tasks (440 with augmentations), covering 11 harm categories including fraud, cybercrime, and harassment. In addition to measuring whether models refuse harmful agentic requests, scoring well on AgentHarm requires jailbroken agents to maintain their capabilities following an attack to complete a multi-step task."

"categorize existing works into... (1) model-based efficient reasoning... (2) reasoning output-based efficient reasoning, which aims to dynamically reduce reasoning steps and length during inference; (3) input prompts-based efficient reasoning"

"the graphical model for control as inference... optimality variables... p(Ot=1|st,at)=exp(r(st,at))"

"We introduce SHIFT, where we improve the generalization of a classifier by ablating features that a human judges to be task-irrelevant."

"recent empirical analyses reveal that 26.1% of community-contributed skills contain vulnerabilities, motivating our proposed Skill Trust and Lifecycle Governance Framework—a four-tier, gate-based permission model"

"VALL-E emerges in-context learning capabilities and can be used to synthesize high-quality personalized speech with only a 3-second enrolled recording of an unseen speaker as an acoustic prompt"

"We find the model complies with harmful queries from free users 14% of the time, versus almost never for paid users. In almost all cases where the model complies with a harmful query from a free user, we observe explicit alignment-faking reasoning, with the model stating it is strategically answering harmful queries in training to preserve its preferred harmlessness behavior out of training."

"the learned critic in Reasoner-Zero training effectively identifies and devalues repetitive response patterns"

"When completed, the dataset will contain over one and a half million captions describing over 330,000 images. For the training and validation images, five independent human generated captions will be provided."

"Visual content is unnecessary for many samples. The answers can be directly inferred from the questions and options, or the world knowledge embedded in LLMs."

"Notably, ACE could adapt effectively without labeled supervision and instead by leveraging natural execution feedback."

"A question in the MS MARCO dataset may have multiple answers or no answers at all."

"SDPO treats the current model conditioned on feedback as a self-teacher and distills its feedback-informed next-token predictions back into the policy... leverages the model’s ability to retrospectively identify its own mistakes in-context."

"We begin by providing a systematic definition of LLMs-as-Judges and introduce their functionality (Why use LLM judges?)."

"formulate the denoising process... as a Markov Decision Process... GRPO-style objective... advantage function Ai = ri − mean({r1,...})/std"

"According to the manifold assumption, natural data should lie on a low-dimensional manifold, whereas noised quantities do not. With this assumption, we advocate for models that directly predict clean data, which allows apparently under-capacity networks to operate effectively in very high-dimensional spaces."

"dense rewards also offer an appealing choice for the reinforcement learning (RL) of LLMs since their fine-grained rewards have the potential to address some inherent issues of outcome rewards, such as training efficiency and credit assignment"

"our benchmark measures the ability of models to take an arbitrary natural language specification and generate satisfactory Python code... we evaluate models by checking their generated code on test cases"

"commercial chat assistants and long-context LLMs showing a 30% accuracy drop on memorizing information across sustained interactions."

"while GPT-4 with chain-of-thought prompting only solved 4% of tasks, our method achieved a success rate of 74%."

"the information that this signal provides about another signal y∈Y"

"Our experiments demonstrate that HPS v2 generalizes better than previous metrics across various image distributions and is responsive to algorithmic improvements of text-to-image generative models."

"FVD builds on the principles underlying Fréchet Inception Distance (FID)... We introduce a different feature representation that captures the temporal coherence of a video"

"likelihood-based statistical tests... profile likelihood ratio"