Knowledge catalogue
arXiv:2606.05632v1 Announce Type: new Abstract: Within the past few years, the ability of Large Language Models (LLMs) to generate formal mathematical proofs has improved drastically. We provide a com
arXiv:2606.05522v1 Announce Type: cross Abstract: Recent advancements in Large Language Models (LLMs) have shown promising results in music understanding and generation tasks. However, existing works
Fireworks Training Platform keeps expanding. Leading US open weight model Nemotron 3 Ultra is now ready for post-training: SFT and DPO via LoRA or full-parameter, on the same infrastructure that serve
Four papers out recently: 1. http://political-manipulation.ai: Measures and reduces political bias in LLMs; Claude is especially biased 2. http://aibetrayal.com: The public can insert backdoors into A
arXiv:2606.05844v1 Announce Type: cross Abstract: Rule-based Intrusion Detection and Prevention Systems (IDPS) offer precise attack detection as well as mitigation, however their manually crafted, sig
arXiv:2606.05187v1 Announce Type: cross Abstract: Among the many challenges hindering the responsible development and deployment of AI, arguably none has faced more intense scrutiny than bias in its v
arXiv:2606.05332v1 Announce Type: new Abstract: Patch-based Time Series Foundation Models (TSFMs) suffer from context poisoning: structurally anomalous patches capture disproportionate attention and s
arXiv:2606.06468v1 Announce Type: new Abstract: We introduce Goedel-Architect, an agentic framework for formal theorem proving in Lean 4 centered on blueprint generation and refinement. A blueprint is
arXiv:2606.05566v1 Announce Type: new Abstract: Large Language Models (LLMs) have transformed natural language processing, but they remain vulnerable to Prompt Injection (PI) and Jailbreak (JB) attack
arXiv:2606.05256v1 Announce Type: new Abstract: This study analyzes a publicly released dataset from a discontinued field experiment on Reddit's r/ChangeMyView. The intervention, conducted by unknown,
arXiv:2606.05316v1 Announce Type: new Abstract: Multimodal memes are dynamic and often require up to date background knowledge for interpretation. Existing methods often overlook such knowledge or rel
I want AI to succeed, and have been positive about many systems (Claude Code, AlphaFold, AlphaGeometry, Cicero, etc). It’s not AI that I hate; it’s bullshit and greed that I despise. Not my fault that
Introducing Harness-1, a 20B search agent trained with a state-externalizing harness. > frontier-level long-horizon search, rivaling Opus-4.6 and outperforming GPT-5.4 > Context-1-level cost and laten
it’s a bad day when @scaling01 goes all Gary Marcus on the media 🤣 This is a good example of how AI news gets distorted. The example is from Tagesschau, the most watched news program in Germany. Anthr
“I've tried to find where this stops being circular and I can't.” 🦔Google signed a deal to pay SpaceX 920 million a month for access to 110,000 Nvidia GPUs at SpaceX data centers. The contract runs Oc
arXiv:2507.12612v3 Announce Type: replace-cross Abstract: Supervised fine-tuning performance for large language models depends strongly on how training budget is distributed across a heterogeneous set
arXiv:2606.05861v1 Announce Type: cross Abstract: The rapid development of large language models(LLMs) has led to remarkable advances in natural language processing. However, the increasing scale of t
arXiv:2606.06036v1 Announce Type: new Abstract: Despite recent progress, LLM agents still struggle with reasoning over long interaction histories. While current memory-augmented agents rely on a stati
arXiv:2606.05429v1 Announce Type: new Abstract: Post-training quantization (PTQ) is critical for the efficient deployment of large language models (LLMs). Recent ultra-low-bit PTQ methods rely on rigi
arXiv:2606.05613v1 Announce Type: new Abstract: The rapid evolution of Large Language Models (LLMs) has established cross-lingual versatility as a defining feature of modern systems. However, fine-tun
arXiv:2602.13697v2 Announce Type: replace Abstract: Relational databases (RDBs) contain vast amounts of heterogeneous tabular information that can be exploited for predictive modeling purposes. But si
arXiv:2606.06021v1 Announce Type: cross Abstract: On-policy distillation (OPD) supervises the student only in output space by matching next-token probabilities. This output-only paradigm has two limit
arXiv:2606.06470v1 Announce Type: cross Abstract: We propose a preconditioning (PC) layer, a weight parameterization via polynomial preconditioner that ensures stable weight conditioning throughout LL
arXiv:2605.12376v2 Announce Type: replace Abstract: Table processing-including cleaning, transformation, augmentation, and matching-is a foundational yet error-prone stage in real-world data pipelines
arXiv:2606.05463v1 Announce Type: new Abstract: Patient safety event triage, determining whether a clinical event is reportable under jurisdiction-specific policy, is a high-stakes task typically perf
arXiv:2606.05888v1 Announce Type: new Abstract: Retry-based objectives such as pass@K and max@K optimize the best return obtained from multiple sampled trajectories, and recent work has shown that the
arXiv:2605.04733v2 Announce Type: replace Abstract: Text-based role-playing models can imitate character styles, but often fail to capture scene atmosphere and evolving tension, which are crucial for
arXiv:2601.09236v3 Announce Type: replace-cross Abstract: Reward design remains a significant bottleneck in applying reinforcement learning (RL) to real-world problems. A popular alternative is reward
I've been experimenting with different approaches to running code in a sandbox for several years now, but my latest attempt feels like it might finally have all of the characteristics I've been lookin
arXiv:2606.05614v1 Announce Type: new Abstract: Large language models (LLMs) are rigorously aligned to refuse harmful requests, a process that inherently cultivates a latent capacity to evaluate and r
arXiv:2606.05754v1 Announce Type: cross Abstract: Phase-sensitive optical time-domain reflectometry (phi-OTDR) is widely used in large-scale distributed acoustic sensing (DAS) because it provides dist
arXiv:2606.05525v1 Announce Type: new Abstract: Recent advances in agentic visualization have enabled the translation of natural language into executable scientific visualization (SciVis) workflows. W
arXiv:2606.05241v1 Announce Type: cross Abstract: Public benchmarks enable fair and reproducible evaluation of LLM reasoning, but they become fragile for deep research agents that actively search the
⚠️⚠️ Seismic shift ⚠️⚠️ It’s a good day to be Mistral. Nobody is going to trust an American AI company that is partly owned by the US Government. Just the way the US doesn’t trust Huawei. After this m
arXiv:2606.05434v1 Announce Type: cross Abstract: Group Relative Policy Optimisation (GRPO) has emerged as an effective reinforcement-learning algorithm for aligning language models on reasoning tasks
arXiv:2606.05342v1 Announce Type: new Abstract: AI agents are increasingly asked to carry out work that spans minutes, hours, or longer. Yet the default model of agent behavior is continuous action: i
“.. So now Google and Anthropic pay rent on the hardware Grok couldn't use, and that rent is the AI revenue story SpaceX takes public on Thursday.” 🦔Google signed a deal to pay SpaceX 920 million a mo
Spent more time learning deepagents from @LangChain with primary focus on integrating MCP servers with auth that doesn't conform completely to the OAuth standard. ( In prep of a work coming my way ) B
SpaceX's Starlink satellite launches have become the dominant source of orbital launches, exceeding the combined launch activity of all other satellite operators and launch providers. This milestone r
arXiv:2606.05464v1 Announce Type: new Abstract: Verifiable reward training has improved mathematical and coding reasoning, but these domains capture only part of step-by-step decision making. Many rea
arXiv:2606.06333v1 Announce Type: cross Abstract: Sparse Autoencoders (SAEs) are widely used for mechanistic interpretability in large language models, yet their formulation assigns each latent featur
arXiv:2602.00911v2 Announce Type: replace Abstract: The unit of collaboration in federated learning determines what guarantees are even expressible. Flat units like weights, prompts, raw examples, car
arXiv:2606.05382v1 Announce Type: new Abstract: Multi-table question answering requires models to retrieve relevant evidence, link schemas, and perform compositional reasoning across relational tables
arXiv:2606.05784v1 Announce Type: new Abstract: We identify and formally characterize credit misassignment as a systematic failure mode of GRPO in tool-augmented multimodal search agents: its uniform
arXiv:2606.05608v1 Announce Type: cross Abstract: For over half a century, software engineering has operated on a foundational premise: human engineers decompose problems, encode decision logic into s
The Gemini Pro models do not seem to be iterating anywhere near as quickly as Claude or GPT (last release was 3.1 Pro in February). Its causing a growing performance gap between Google and the other t
arXiv:2606.06133v1 Announce Type: cross Abstract: TLA+ is a formal specification language for verifying distributed systems and safety-critical protocols. Large language models (LLMs) frequently produ
arXiv:2606.06337v1 Announce Type: new Abstract: Large language model (LLM) deployments for long-horizon tasks face a fundamental constraint: context windows are finite while productive work sessions a
arXiv:2606.06284v1 Announce Type: new Abstract: Large language model agents increasingly rely on external tools, but larger tool menus can reduce reliability and efficiency by increasing wrong-tool ca
arXiv:2606.05403v1 Announce Type: cross Abstract: Language models increasingly act as epistemic proxies, synthesizing evidence from multiple sources to inform decisions. Whether they evaluate the qual
VLA-JEPA just dropped in LeRobot 🤖 What makes this model special is that it does not just learn what action to take from a given observation, it also leverages a JEPA world model to learn action-relev
arXiv:2606.06453v1 Announce Type: new Abstract: Sparse attention is becoming increasingly important for serving large language models (LLMs) as generation lengths continue to grow. However, deploying
arXiv:2606.05304v1 Announce Type: new Abstract: Multi-agent systems (MAS) built on large language models are typically organized around roles, pipelines, and turn schedules, while the content that age
arXiv:2606.06055v1 Announce Type: new Abstract: Long-term memory enables language model agents to support personalized interactions, but it remains unclear when available memories warrant integration
arXiv:2606.05806v1 Announce Type: new Abstract: Existing benchmarks evaluate Tool-Integrated Reasoning (TIR) in LLMs on idealized ''happy paths'', largely overlooking real-world tool failures. We intr
arXiv:2606.06460v1 Announce Type: cross Abstract: As autonomous LLM agents increasingly hold real credentials and operate infrastructure without a human in the loop, operators have no standard way to
This post shows a completed Wordle game (#1,812) solved in 4 attempts, displaying the colored tile feedback pattern (gray for incorrect letters, yellow for correct letters in wrong positions, green fo
arXiv:2606.06147v1 Announce Type: new Abstract: End-to-end Vision-Language-Action (VLA) models have shown promise in UAV navigation. However, existing approaches typically rely on historical observati
You can’t let this happen, @DavidSacks, cc @elonmusk. It’s WWWIII but with AI. Nobody wins. ⚠️⚠️ Seismic shift ⚠️⚠️ It’s a good day to be Mistral. Nobody is going to trust an American AI company that
Your margin is my opportunity: AI version… The biggest surprise of 2026 is that the capability gap between the best open-weight/source models and the best closed models has narrowed much faster than t