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Search: “in-context learning”

6 stories in the last 7d

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Convergent Emergence of In-Context Learning Across Modalities

Controlled experiments show few-shot in-context learning emerges across six modalities including language, genomes, images, and proteins, partially supporting a convergence hypothesis.

The paper tests the Convergent Emergence Hypothesis: that few-shot in-context learning, when it emerges, shares a common cross-modality difficulty profile. A controlled framework instantiated the same task suite across six modalities: language, genome, integer sequences, time series, images, and proteins. Paired-mapping ICL emerged in all six modalities, surpassed controlled baselines, and showed correlated per-task effects in five of them, providing partial support for the hypothesis.

Hugging Face daily papers · 6d agoAI research

In-Context Robot Learning with VLM Agents

GPT-Policy uses commercial VLM agents like GPT-6 Astra for in-context robot learning, translating demonstrations and feedback into verified robot actions without gradient updates.

The paper (arXiv 2609.19138) presents GPT-Policy, a framework combining a context compiler that preserves task-relevant visual transitions, a VLM such as GPT-6 Astra that proposes robot-tool actions, and a constrained controller that verifies and executes each action. Real-robot trials show human video demonstrations improve task completion even without robot action labels, while aligned action references yield further gains on contact-sensitive tasks. Evaluation covers success and efficiency metrics, matched model comparisons, and controlled context ablations.

Hugging Face daily papers · 2d agoAI research1

Nums AI Releases Causilo: A Tabular Foundation Model That Tops TabArena Among Single Models

Nums AI released Causilo, an Apache-2.0 tabular foundation model achieving the highest single-model Elo (1794) on TabArena for classification and regression.

Nums AI released Causilo 1.0.1, a pretrained in-context learning tabular foundation model for classification (up to 10 classes) and regression, with Apache-2.0 code and research-only weights on Hugging Face. It achieved the highest single-model TabArena Elo of 1792.9 overall, beating TabFM (1764.4) and EXAONE Tabular (1758.8), and a maintainer re-run placed it 3rd of 88 including system entries. It also ranked first by CRPS, R² and RMSE on ScoringBench across 101 datasets, and was fastest on fit and predict versus TabICLv2 and TabPFN-3 on an H100 GPU at 8.15 GiB memory. The model was pretrained only on synthetic data, uses cross-attention to keep cost linear in feature count, and version 1.0.1 adds quantile outputs via 999 native quantiles.

MarkTechPost · 2d agoModel release

Large Language Models Develop Belief State Geometry In-Context

Probing six open-source LLMs on HMM-generated data shows belief states are linearly decodable (R² 0.83–0.99), suggesting in-context learning approximates Bayesian prediction.

Researchers prompted six open-source LLMs with data from 40 hidden Markov models selected for non-trivial belief structure and probed residual-stream activations for belief states (posteriors over hidden states). Belief states were linearly decodable with peak R² values of 0.83–0.99 across HMM/LLM combinations, spanning early to late layers. Patching and steering the probe-identified subspace preserved downstream prediction quality while control interventions degraded performance substantially, establishing functional relevance. The results provide representation-level evidence that in-context learning approximates optimal Bayesian prediction over a context-inferred generative model.

arXiv cs.AI / cs.LG / cs.CL · 2d agoAI research1

LimiX-2: A Contextual Mechanism Network Towards General Structured-Data Intelligence

LimiX-2, a tabular foundation model built on Contextual Mechanism Networks, outperforms existing tabular models on TabArena, TALENT, and BCCO.

Researchers introduced LimiX-2, a new model in the LimiX family that adopts the Contextual Mechanism Networks (CMNs) paradigm and is pretrained with Context-Conditional Masked Modeling (CCMM) on synthetic datasets generated by structural causal models. Unlike tabular PFNs centered on p(y | x, D_context), CMNs learn mechanism-oriented joint modeling of p(x, y | D_context). Evaluations on TabArena, TALENT, and BCCO show LimiX-2 outperforms current dataset-specific models and tabular foundation models. Its feature attention also encodes direct causal relationships, enabling accurate causal skeleton recovery.

Hugging Face daily papersupdated · 2d agofirst · 3d agoAI research 2 sources

Prior Labs Releases TabPFN-3.5: A Tabular Foundation Model That Beats the Winning Otto Kaggle Solution With Default Settings

Prior Labs releases TabPFN-3.5, a 220M-parameter open-weights tabular foundation model that beats the 2015 Otto Kaggle winning score with default settings.

Prior Labs released TabPFN-3.5, a tabular foundation model that predicts in a single forward pass without per-dataset training or tuning. The base model grew from 53M to 220M parameters with a single multitask checkpoint, learned Fourier features, and in-context ECDF rank encodings. It scores 0.375 on the 2015 Otto Kaggle private leaderboard versus the winning 0.382 and claims first place on seven tabular benchmarks including TabArena and BeyondArena. Open weights cover the base, Fast (84M), and Thinking variants, but production use requires the Prior Labs API or a commercial license.

MarkTechPost · 2d agoModel release1