Showing papers from Technion Show all papers
Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026
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Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026
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Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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Adaptive batching policies process multi-step lookahead via state-dependent batches, yielding near-optimal regret bounds for tabular reinforcement learning.
Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Value-filtered decoding selectively steers LLM generation using a value-based safety criterion with explicit false-intervention bounds, improving safety-utility trade-offs over baselines.
Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 4 on Hugging Face
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STRABLE introduces 108 real-world string-and-number tables and benchmarks 445 pipelines, finding simple embeddings with advanced learners suffice for categorical tables while LLMs help on free-text tables.
Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 4 on Hugging Face
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MulTaBench benchmarks 40 multimodal tabular datasets and shows target-aware tuning of text and image embeddings improves predictive performance over frozen embeddings.
Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026 · ▲ 142 on Hugging Face
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Deriving reduced ODEs for low-rank RNN learning reveals loss-invisible overlaps that encode training history and expose hidden connectivity differences.
Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Controllable user simulation is formalized as causal inference, proving supervised fine-tuning injects look-ahead bias causing geometric variance explosion and controllability collapse, with proposed mitigations restoring consistency and robust generalization.
Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 1 on Hugging Face
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Applying CVaR to the immediate belief cost targets per-step state uncertainty while preserving standard MDP structure, enabling any expectation-based planner to become risk-sensitive with unchanged algorithms and end-to-end finite-time guarantees.
Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Graph Sparse Sampling shares sampled futures across actions to avoid exponential horizon dependence in continuous MDP planning, with polynomial sample bounds and strong long-horizon control performance.
Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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SP-CACW minimizes an upper bound on a target client's convergence error via convergence-aware weighting that trades peer bias against variance and excludes harmful peers.
Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026
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DEMASK predicts token dependencies in discrete diffusion language models to select weakly dependent masked positions for parallel unmasking, bounding sampling error and accelerating Dream-7B by 1.7, 2.2× with preserved accuracy.
Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Block Sparse Flash Attention accelerates long-context inference by computing exact similarities to select top-k value blocks, skipping ~50% of computation for up to 1.38x kernel and 1.24x end-to-end speedups with minimal accuracy loss.
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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A framework combines multi-armed bandits with low-rank predictions to build doubly robust estimators and valid confidence intervals for identifying the best LLM with fewer evaluations.
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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A mixed-integer optimization framework trains interpretable classifiers that bound intersectional bias below acceptable thresholds across protected subgroups.
Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026
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INTRA unifies retrieval and generation via decoder attention over internal encoder states, outperforming engineered RAG on question-answering benchmarks.
Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026 · ▲ 10 on Hugging Face
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Strategic classification can make VC dimension 1 problems unlearnable, but geometric definability via first-order formulas over real exponentiation preserves learnability with controlled sample complexity.
Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026
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Normalizing weights and hidden states to the unit hypersphere makes nGPT robust to 4-bit arithmetic, enabling stable end-to-end NVFP4 training without extra scaling or transforms.
Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026 · ▲ 2 on Hugging Face
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